Open access peer-reviewed chapter

Malaria Transmission in South America—Present Status and Prospects for Elimination

Written By

Jan Evelyn Conn, Maria Eugenia Grillet, Margarita Correa and Maria Anice Mureb Sallum

Submitted: 24 January 2018 Reviewed: 03 April 2018 Published: 18 July 2018

DOI: 10.5772/intechopen.76964

From the Edited Volume

Towards Malaria Elimination - A Leap Forward

Edited by Sylvie Manguin and Vas Dev

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Abstract

Four countries (Brazil, Colombia, Peru, and Venezuela) together contributed ~80% of the 875,000 malaria cases reported in the Latin American region (2016). During the 10-year period (2005–2015) when global malaria incidence was dramatically reduced, Brazil and Colombia were an integral part of this trend, on track to meet the mid-term 2020 goal established by the World Health Organization. In Colombia, since 2015 at the cessation of a five-year globally funded malaria program, both incidence and proportion of Plasmodium falciparum infections have increased, mainly due to the budget constraints. Similarly, despite a strong record and major recognition for reducing malaria, in 2017, Brazil has seen a resurgence of malaria cases, but no increase in the proportion of Plasmodium falciparum to P. vivax. A globally funded malaria control program in Peru from 2005 to 2010 resulted in appreciable reduction in the annual parasitic incidence down to 1/1000 by 2011–2012, but soon after, the annual malaria incidence began to rise and by the end of 2017, there were 53,261 reported cases. To add to Venezuela’s political and financial woes, malaria continues to increase, such that, 300,189 cases were reported by the end of week 42, 2017. The only rational pathway to malaria elimination is sustained nation-level financial support that does not fall prey to political vicissitudes.

Keywords

  • malaria
  • Brazil
  • Colombia
  • Peru
  • Venezuela
  • epidemiology
  • transmission landscape
  • vector biology
  • interventions

1. Introduction

Malaria transmission control and eventual elimination is one of the greatest worldwide challenges in public health. The World Health Organization (WHO) has established a well-delineated and ambitious plan for control and elimination of the disease by 2030 [1], with a mid-term 2020 global target of reduction of at least 40% in malaria case incidence and malaria mortality rate. Significant advances were made in most of the endemic countries in Latin America, particularly from 2000 to 2015 [2], when the incidence of cases declined by 62% (1,181,095 in 2000 to 451,242 in 2015) and malaria-related deaths by 61.2% (410 to 159). The main strategies used have been rapid diagnosis, treatment with artemisinin-based combination therapy (ACT), indoor residual spraying (IRS), and insecticide-treated bednets (ITNs) or long-lasting insecticide-treated nets (LLINs) [3, 4].

However, malaria is still an important public health concern in the whole Neotropical region, more so during 2016, when a substantial increase in case incidence (875,000) was estimated [1]. Of the 18 endemic countries of Latin America, nine showed an increase in cases of more than 20% compared to 2015 [5], whereas the highest percentage increase (36%) of change in case incidence rate took place in 2014–2016. This was mainly due to the situation in Venezuela. In 2016, Venezuela (34.4%) and Brazil (18%) together accounted for more than 50% of the total reported cases, followed by Colombia (15.3%) and Peru (14.3%). According to the WHO report [1], malaria cases in Colombia nearly doubled in 2016 compared to 2015, despite an earlier reduction; in Peru cases have also been rising steadily since 2011, which has resulted in a loss of the gains achieved since 2000. In Venezuela, there has been a persistent increase in cases since 2000 and even more so since 2015 due to economic and political mismanagement [6] and Guyana recorded an increase in the proportion of P. falciparum (42%) to P. vivax cases (58%), the highest in South America [1, 7]. In contrast, Suriname observed declining malaria transmission trends to near-elimination levels through a rigorous control and education campaign, together with fortuitous flooding that destroyed populations of the primary malaria vector in the interior [8]. In 2016, Suriname reported only seven cases of P. falciparum and 69 of P. vivax [1].

The malaria landscape in Latin America consists of low transmission interspersed with diverse hot-spots where transmission is spatially and temporally focused [4, 9, 10, 11]. At a regional scale, reported malaria cases where the Annual Parasite Index (API) is >100 are concentrated in the municipalities of Bolívar, Delta Amacuro, and Sucre (Venezuela); Acre, Amapá, and Amazonas (Brazil); Amazonas, Antioquia, Chocó, and Vichada (Colombia); and Loreto (Peru) [1]. Nine countries reported zero local P. falciparum cases; Bolivia and Guatemala reported <10 cases. Twelve countries (Argentina, Paraguay, Costa Rica, Belize, Mexico, French Guiana, Suriname, Dominican Republic, Honduras, Bolivia, Haiti, and Brazil) are projected to have attained ≥40% reduction in case incidence by 2020, and five (El Salvador, Ecuador, Guatemala, Guyana, and Colombia) are on target for 20–40% reduction [1].

Currently, an estimated 102 million people are living in areas at risk of malaria transmission in Latin America, of which at least 28 million live in high-risk localities (>10 cases/1000 inhabitants). Most malaria cases in South America result from P. vivax (69%) infections, followed by P. falciparum (27%), and most occur in the Amazon rain forest. Colombia differs from most of its neighbors in having a large proportion of malaria transmission outside the Amazon, such as the northwest, along the Pacific Coast and in the east, bordering Venezuela [12]. There has been renewed interest in understanding the biology, epidemiology, and the specific challenges of P. vivax, particularly since the decline of P. falciparum [4, 13, 14, 15]. Plasmodium malariae, responsible for <1% of cases in this region, is rarely considered in malaria reports, but is likely underestimated because it is difficult to diagnose using microscopy, has a slow growth rate, is generally asymptomatic in humans, and is considered less pathogenic compared with P. falciparum and P. vivax [2].

To stay on track and advance towards elimination, some of the main challenges in this region, identified by WHO (2017), are a lack of sustainable and predictable international and domestic funding, risks posed by political conflict in malaria endemic zones (e.g., Venezuela), environmental change and anomalous climate patterns [16, 17, 18, 19], the emergence of parasite resistance to antimalarials [20, 21, 22], and insecticide resistance in mosquito vectors (reviewed in [23, 24]). Additional regional challenges to ongoing efforts to decrease malaria incidence include a significant rise in malaria cases in recent years in Venezuela [6], evidence of submicroscopic and asymptomatic infections [25], increases in peri-urban and gold mining-related malaria [26], and an upsurge in cases of P. falciparum in Colombia and Peru [1, 2].

Throughout this chapter, we adopt the new nomenclature proposed for the subfamily Anophelinae by Foster and collaborators [27]. Consequently, Anopheles (Nyssorhynchus) darlingi is herein referred to as Nyssorhynchus darlingi. The most important Nyssorhynchus vectors involved in this malaria landscape epidemiology are anthropophilic and/or opportunistic and ecologically/behaviorally variable [28]. Patterns of transmission vary regionally, depending on climate, biogeography, ecology, and anthropogenic activities. Transmission is exacerbated by deforestation for timber extraction, agricultural settlements, and mining and development of dams for hydroelectric projects. The creation of breeding sites (such as fish ponds, microdams, forest streams blocked by road construction, and mining pools) [29, 30, 31] and spatial mobility of humans, where there is little public health infrastructure (if any), also facilitate transmission in endemic malaria regions and beyond [32, 33, 34]. Factors such as infectivity of vectors by P. vivax or P. falciparum at levels rarely above 1% and heterogeneous entomological inoculation rates (EIRs) combined with low-to-moderate human blood indices (HBI) can result in high-risk for malaria transmission in certain habitats, often associated with anthropogenic change [29, 35, 36]. Inadequate housing protects no one and is a major impediment for reducing and ultimately ending human-mosquito contact [37].

The main objectives of this chapter are: (1) to evaluate the available intervention options that may be generalizable among the main vector species, (2) to determine scenarios where hot-spot-specific vector biology and ecological interventions have the best prospects for success, and (3) to propose ways to test and combine current and novel interventions against the diversity of malaria vector species and habitats. This chapter focused on the four countries that together contributed the highest proportion (81.6%) of all reported malaria cases in Latin America in 2016, namely Venezuela, Brazil, Colombia, and Peru [1].

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2. Current malaria situation

2.1. Brazil

Brazil had been reporting the highest number of malaria cases in Latin America for many years, but this shifted in 2015. Venezuela, with the growing economic and political crisis, had the dubious distinction of the highest estimated incidence of malaria in the region [38]. Recently, Brazil reported the second highest number of malaria cases (18%), down from 24% of cases in 2015 [1, 38]. Furthermore, Brazil recorded a 76.8% decrease in malaria incidence during 2000–2014 [4], even though transmission was observed to be ongoing in 808 municipalities in 2013 [13]. Nearly all malaria cases (99.5%) in Brazil are reported in the Amazon region, an enormous territory that covers an estimated 60% of Brazil and consists of nine States: Acre, Amazonas, Amapá, Maranhão, Mato Grosso, Pará, Rondônia, Roraima, and Tocantins [4]. The State with the most malaria cases and highest API since 2005 is Acre; the region within Acre with the highest-risk cluster is Vale do Juruá [39] including the municipalities of Cruzeiro do Sul, Mâncio Lima, and Rodrigues Alves that are persistent malaria hot-spots [40]. Other States with API >50 as of 2015 include Amapá, Amazonas, Pará, and Roraima (Figure 1).

Figure 1.

Geographical location of municipalities in Brazil, Colombia, Peru and Venezuela reporting Annual Parasite Index (API) >50 for data based on 2015 [38, 41].

Across the Brazilian Amazon, the proportion of P. falciparum cases has been declining steadily for several years (Table 1), and in 2015, this parasite comprised approximately 11% of all cases, with P. vivax responsible for the remaining 89% [4]. In 2015, the Brazilian Ministry of Health (MOH) launched The Plan for Elimination of Malaria in Brazil, which focuses on the elimination of P. falciparum [46]. It is comprehensive, but substantial challenges remain: behavioral heterogeneity of the primary vector Ny. darlingi means that LLINs are only partially effective; most Amazonian housing structures do not meet criteria for routine IRS application; larviciding is most effective for accessible stagnant water bodies, e.g., fish ponds, especially those associated with hot-spots, but not effective for many natural water bodies, which may be difficult to identify and reach, or for streams and rivers with slow-moving water, which are typical Ny. darlingi habitats [47, 48]. By the end of 2016, P. falciparum still accounted for 11% of all malaria infections reported, and near the end of 2017, this was 10.8% (Table 1). In 2016–2017, Brazil was challenged by malaria resurgence, including in municipalities that were in the prevention phase and others with low malaria transmission. Furthermore, the total number of malaria cases in Brazil has increased from 105,057 cases during the period January 1 to December 31, 2016, to 154,343 cases during the period January 1 to October 31, 2017, an increase of 47% [42].

Country 2014 2015 2016 2017
Number of malaria positive cases Number of malaria positive cases Number of malaria positive cases Number of malaria positive cases
P. vivax P. falciparum P. vivax P. falciparum P. vivax P. falciparum P. vivax P. falciparum
Brazil 117,009 22,234 122,743 15,445 110,343 13,829 172,876 21,017
Colombia 20,129 20,634 21,987 26,061 32,635 49,974 22,405 29,404
Peru 54,819 10,416 49,287 12,569 41,287 15,319 40,564 12,697
Venezuela 62,850 27,843 100,880 35,509 179,554 61,034 246,859 53,330

Table 1.

Number of malaria cases of Plasmodium vivax and P. falciparum in Brazil, Colombia, Peru, and Venezuela (2014–2017) [1, 42, 43, 44, 45].

Note: Source of malaria case numbers 2014–2016 is WHO (2017); 2017 data are from individual Ministry of Health websites from each of the four countries.

Some of the roadblocks in reducing and eliminating P. vivax include the high frequency of low-density P. vivax infections and the difficulty of their diagnosis by microscopy, particularly in areas approaching elimination and the persistence of liver stage hypnozoites that may be responsible for relapses [2, 4, 49]. Peri-urban and urban malaria transmission has been difficult to eliminate in cities such as Manaus (Amazonas State) and Cruzeiro do Sul (Acre State). In 2015, Manaus reported 7300 cases, most of which were acquired during work or other activities in neighboring municipalities, suggesting that interventions need to be focused on the mobile proportion of the human population [13]. Better transmission control is thought to lead to a lower P. falciparum:P. vivax ratio, reflecting the rapid and stable reduction of cases in urban settings compared with a lower and more heterogeneous reduction in rural and indigenous areas [13]. In a study based in and around the small cities of Mâncio Lima and Rodrigues Alves, Acre State; three development gradients, i.e., urban-rural, rural-riverine, and housing location were analyzed for multiple households. The lowest risk (OR = 0.55, 1.23–1.12) of having a household with malaria was along the rural-riverine gradient, the most forested of the three; in contrast, the highest risk (OR = 1.92, 1.03–3.92) was along the urban-rural gradient, where urbanization was associated with roads, basic services, water treatment, electricity from a power grid, and less forest access [40]. This is an interesting and important finding, because malaria is so often assumed to be rural, associated with nearby water bodies and often linked to the forest environment. However, malaria risk is clearly linked with poverty, as another important finding of this study was that malaria risk is higher for poor individuals living in rural areas than those living in urban areas [40]. The poor in urban areas generally are exposed less frequently to biting, infected Nyssorhynchus and Anopheles mosquitoes, and have better access to health services than the poor in rural areas [40].

A valuable epidemiological tool was developed in 2010 to identify malaria outbreaks via an automated algorithm [50]. Use of the algorithm aimed to mobilize local control managers to act as rapidly as possible and they identified P. vivax as the primary causative pathogen for nearly all outbreaks, most of which occur in low or interrupted transmission areas where the likelihood of reintroduction is high. In 2014 and 2015, as many 112 and 111 outbreaks were identified, respectively [13]. The effectiveness of this tool has not been validated but it demonstrated usefulness in transmission reduction, which could lead to widespread adoption in Brazil.

2.2. Colombia

In 2016, Colombia recorded 83,227 cases, the third highest number in Latin America, which comprised 15.3% [1, 41]. Thus, malaria continues to be a serious public health problem and transmission is heterogeneous, presenting zones of low unstable transmission with endemic-epidemic patterns including various hot-spots [12]. From 2000 to 2014, Colombia made solid gains against malaria (50–75% reduction in cases), mainly due to interventions such as diagnostic health posts and vector control. However, these gains have been undermined since the Colombia Malaria Project ended in 2015; case numbers doubled between 2015 and 2016 [41].

For the past decade, P. vivax accounted for approximately 70% of reported cases, with the remainder exclusively P. falciparum [12]. However, in 2016, this proportion shifted alarmingly in favor of P. falciparum constituting 60% of reported cases [1, 41, 43, 51, 52]. This parasite species predominates along the Pacific Coast, one of the endemic hot-spots, where there is a high occurrence of Colombian Afro-descendant individuals who are Duffy-negative [53].

Taken together, eight Colombia Departments accounted for 90.8% of all the 2016 noncomplicated malaria cases. These are Chocó, Nariño, and Cauca (western Colombia), Antioquia and Córdoba (northwestern), Guainía and Vichada (central-eastern along the border with Venezuela), and Amazonas (southeastern). Among various Departments, Chocó was worst affected and contributed 53% of all reported cases during 2014–2015 [38]. Nevertheless, up to the 49th epidemiologic week of 2017, Chocó registered a lower proportion of cases (30.7% [43]) compared with the same period in 2015, because several health posts ceased reporting due to national, State, and municipal budgetary constraints with the closure of the Colombia Malaria Project (2015). In the Departments of Arauca and Guajira in eastern Colombia, bordering Venezuela, there was an increase in cases compared to the average number registered during 2012–2016. Of the 860 non-autochthonous cases reported overall, most (76.7%) were P. vivax and nearly all (93.1%) were from Venezuelan patients [43].

Malaria transmission in Colombia has mainly been rural, but a recent study indicated that between 2008 and 2012, urban and peri-urban malaria transmission described as endemic, unstable and of low intensity, occurred in many municipalities in the Pacific Coast and a few in eastern Colombia [53]. However, the authors indicated that a serious limitation was not having a clear consensus on the definition of urban and peri-urban. Nevertheless, there appears to be a trend of decreasing rural and a concurrent progressive increase of urban malaria. Possible explanations of this phenomenon are human migration resulting from ongoing-armed conflict, illegal mining, or illicit crop activities, and the movement of asymptomatic carriers.

In western and northwestern Colombia, with the existing healthcare and disease prevention programs, gold-mining (mostly illegal) has played an important role in the maintenance of malaria as shown by public health surveillance data based on 2010–2013 [26]. This study showed that gold-mining was predominant in seven Colombian Departments that contributed 89.3% (270,753 cases) of the national malaria cases during this period; of which, 31.6% of the cases were from mining areas. The worst of these were located in Antioquia, Córdoba, and Buenaventura municipalities in Valle del Cauca.

Vector control interventions in Colombia rely on the use of insecticides, larvicides, and ITNs [54] to reduce human-vector contact. Some research groups focused on mosquito vector biology aiming to provide baseline information for the development and implementation of appropriate vector control interventions by the evaluation of ecology and biology of vector species, improved species identification, spatio-temporal distribution, biting behavior and preferences, and natural infection by Plasmodium [55, 56, 57, 58, 59, 60].

A comprehensive early warning system, as part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System at the municipality level, has been implemented in four pilot sites in Colombia, where it showed promise, providing new data on malaria incidence and seasonality, vector species presence and abundance, entomological indices and feeding frequencies, climate variables, human population information, and some data on vector control activities [61]. Limitations that remained included the scarcity and difficulty of accessing cultural qualitative and quantitative factors and the limited preparedness of State and municipal health authorities to implement malaria dynamic models [61].

2.3. Peru

The most recent WHO data showed that Peru reported an estimated 14.3% of all malaria cases in the region for 2016; this amounted to 56,606 cases, of which 73% were P. vivax [1]. This estimate has been rising fairly steadily since 2010–2011, ever since cessation of the international financial support provided by the Global Fund Malaria Project “PAMFRO” that had successfully reduced the annual incidence to <1 case/1000 inhabitants for 2010 and 2011 [62]. After 2011, there was a surprisingly rapid malaria resurgence, hypothesized to be due to: (1) budgetary constraints; (2) the perception that malaria was under control; and (3) a concurrent regional dengue epidemic in Loreto [63]. Transmission may have been worsened due to the historic Loreto flood of 2011–2012 that inundated and damaged many riverine communities [62]. During the period between 2002 and 2013, 79% of cases were P. vivax and 21% P. falciparum [11]. A worrisome trend has been the recent increase in the proportion of P. falciparum in 2016 (27%) and 2017 (24%) (Table 1).

Numerous malaria endemic riverine and highway villages exist near the Iquitos-Nauta highway and along the Itaya and Nanay Rivers to the south and west of Iquitos. Inhabitants of two of these villages, Lupuna and Cahuide, took part in a cross-sectional survey in January 2013 (off-peak malaria season), with census data taken in mid-2012. One substantial determination was that prevalence of P. vivax and P. falciparum was many times higher by packed red blood cell (PRBC)-PCR compared with microscopy (25 vs. 3.6% and 5 vs. 0.2%, respectively) [33]. Routine surveillance, using the more sensitive PCR detection method and treatment that includes individuals with very low parasitemia who maintain local transmission even during the off-peak malaria season, acting as potential parasite reservoirs, could be an effective addition to prompt diagnosis and treatment to further reduce malaria regionally. In addition, the overall heterogeneous distribution patterns of P. vivax and P. falciparum differ sharply in Lupuna and Cahuide, i.e., P. vivax is transmitted more locally within villages and P. falciparum is more often acquired at a distance, related to occupation, and transported on a regional basis [33].

Most years, between 90 and 95% of all malaria cases and 99.4% of P. falciparum are reported from Loreto Department, in northern Amazonian Peru [64]. In 2017, this amounted to 50,702 cases (96.2% of those across Peru); there were also small foci in Amazonas State (822 cases in 2017), west of Loreto, and in San Martin (415 cases in 2017), south of Loreto [64]. There was a serious P. vivax outbreak in the gold-mining region of the southern Amazon, in Madre de Dios and neighboring Ucayali until about 2011 [65], but only 6 cases were reported in Madre de Dios and 79 in Ucayali in 2017 [64]. In Tumbes and Piura, along the northwestern coast, malaria has greatly diminished and what remains is epidemic, sporadic, and peri-urban, likely the result of reintroduction [64, 66, 67, 68].

Loreto Department comprises an estimated 30% of Peruvian territory and there are about one million inhabitants [69]. Malaria transmission is highly seasonal, coinciding mainly with the heavy rainy season (January to June) and Andean snowmelt, that together increase river levels up to 10 m, causing major fluctuations in the abundance of the main regional malaria vector Ny. darlingi [70, 71]. Most malaria infections are found in rural and remote villages whose inhabitants live along the Amazon River, and its many tributaries, in enclosed or partially enclosed wooden houses [62, 72]. There has been increasing recognition, beginning with a ground-breaking study [73], of hyperendemic foci linked to occupational activities (such as timber extraction, farming, and charcoal production) and human mobility [33].

2.4. Venezuela

Whereas the continent achieved a significant decline in malaria-related morbidity (62%) and mortality (61%) between 2000 and 2015 as part of the implementation of the Global Malaria Action Plan 2008–2015 [41], Venezuela, in contrast, was the alarming exception in the region, displaying an unprecedented 365% increase in malaria cases between 2000 and 2015 [6]. In 2016 alone, 240,588 malaria cases were officially reported [1], whereas by the end of 2017, this number had increased to 300,189 total cases [45]. Astonishingly, the number of cases reported in 2017 in Venezuela is higher than that reported in the last 29 years (1988–2016) [74].

Economic and political mismanagement have precipitated a general collapse of Venezuela’s health system creating an ongoing humanitarian crisis with severe social consequences [75, 76]. Consequently, a malaria epidemic has been fueled by financial constraints that prevented the procurement of malaria commodities (insecticides, drugs, diagnostic supplies, mosquito nets, etc.), epidemiological surveillance, reporting activities, vector-control and disease-treatment efforts, high internal human migration associated with illegal gold mining, and underlying malnutrition due to a general lack of provision and implementation of services. In 2016, P. vivax malaria accounted for 76% of all cases, followed by P. falciparum (18%), P. malariae (<1%), and P. vivax/P. falciparum mixed (6%) infections [1].

Although P. falciparum malaria occurs mostly in the lowland rain forests of the Venezuelan Guayana region, P. vivax malaria is endemic in the coastal plains and savannas, as well as the lowland Guayana forests [17]. Currently, an estimated 80% of malaria in Venezuela is associated with gold mining areas in the forest ecosystem of the southeastern region, where local transmission is maintained in few but persistent disease hot-spots by Ny. darlingi and Ny. albitarsis s.l. ([77, 78, 79]; Grillet unpublished). Infection Rates (IR) of Ny. albitarsis s.l. and Ny. darlingi collected during 2009–2012 in Sifontes, Bolivar State, were very high: 5.4 and 4.0%, respectively [80]. Gold mining extraction activities substantially reduce forest vegetation cover, which seems to favor aquatic vector habitat production, especially for Ny. albitarsis s.l. ([79]; Grillet unpublished). Mining activities in turn result in highly mobile human populations that migrate in search of jobs, working, and sleeping outdoors, exposed to continuous mosquito biting for long periods of time. Many of these economic migrants are previously unexposed to Plasmodium and some of them return to nonendemic malaria regions, e.g., near the capital Caracas, with circulating gametocytes, reintroducing Plasmodium to areas where malaria had been eliminated previously [81]. Although, most disease transmission in Venezuela has been rural, recent observations suggest a significant change in the landscape epidemiology of malaria since 2013—urban and peri-urban malaria transmission are now associated with some cities close to Caracas [Grillet unpublished]. Finally, case spillover has overloaded frontier health care infrastructure in Brazil and Colombia where in 2016, 78 and 81%, respectively, of imported malaria cases originated from Venezuela [2]. The continued upsurge of malaria in Venezuela threatens to become uncontrollable, jeopardizing the hard-won gains in the Americas’ elimination agenda and global malaria targets.

For decades, Venezuela was a leader in vector control and public health policies in Latin America, especially after being the first WHO-certified country to eliminate malaria in much of its territory in 1961 as a result of a very aggressive, vertical malaria control campaign [82]. This campaign consisted of the interruption of malaria transmission through systematic and integrative infection and vector control. Additionally, the program included the detailed knowledge of malaria microepidemiology (at local level, case management, consisting of diagnosis, patient treatment, and mass drug administration), mapping malaria cases, malaria health information system updated weekly, community participation through volunteer community health workers, application of larvicides, and sanitary engineering such as housing improvement and water management. This public health success helped to galvanize interest in global elimination [82]. The Venezuelan approach for malaria elimination in the past differs little from current prevention, control and elimination, except that it was implemented in an epidemiological landscape where insecticide and parasite resistance were absent, political will was significant, and government support was very strong. Vector control and case prevention require long-term investment and sustainability without which it is difficult to envision elimination as a viable outcome.

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3. The main malaria vectors

3.1. Nyssorhynchus darlingi

The most widespread and dominant malaria vector in the Amazon region is Nyssorhynchus darlingi (Figure 2) [27, 28, 84, 86]. Localities where Ny. darlingi has been formally incriminated by ELISA or other molecular techniques are shown in Figure 3, although the full distribution of Ny. darlingi extends from southern Mexico through northern Argentina [84]. This species shares several characteristics with invasive species (e.g., Aedes albopictus) and other primary malaria vectors such as An. gambiae s.s., including fast growth, phenotypic plasticity, rapid reproduction, moderate-high dispersal ability, ecological competence, and association with humans [28, 104, 105, 106]. In Loreto Department, Peru, since Ny. darlingi reinvaded, or re-expanded its range into the peri-Iquitos area about 1998 [107], it has spread along numerous Peruvian river drainages to the north and west [70, 108]. In Brazil and Peru, it is ranked the number one vector [4, 29, 109]; in Colombia, it is one of three main vectors, the other two being Ny. albimanus and Ny. nuneztovari [87, 110, 111]; and in Venezuela, it shares top billing with Ny. albitarsis s.l. [77, 78, 80]. A recent review highlights the very low insecticide resistance in Ny. darlingi detected in the Neotropics, i.e., one population in Choco, western Colombia is resistant to DDT, permethrin, lambda-cyhalothrin, and deltamethrin [23].

Figure 2.

Distribution of Nyssorhynchus darlingi (denoted by white dots). Map made in Google Earth Pro [83] using data from the Malaria Atlas Project [84, 85].

Figure 3.

Localities (denoted by yellow dots) where the primary malaria vector Nyssorhynchus darlingi has been reported infected with Plasmodium vivax or Plasmodium falciparum incriminated by molecular methods during 2005 to 2017 [8, 35, 59, 60, 73, 80, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103]. Map made in Google Earth Pro [83, 84].

The distribution in Brazil includes the lowlands of the Amazonian biome, the Cerrado, and the southern Atlantic forest [84, 112, 113]. Nyssorhynchus darlingi is adaptable and flexible in its behavior: exophagic and endophagic; anthropophilic and opportunistic; though generally exophilic [28, 71, 97, 114]. The standard entomological indices range widely across its distribution [71, 80, 96, 97, 103, 114]. One frequently recognized characteristic of Ny. darlingi is the speed with which it colonizes deforested Amazonian patches and a variety of anthropogenic water bodies such as gold mining pools, brick-making depressions, wells, cisterns, and fishponds, as well as natural breeding site types linked to rivers or flooded forest [29, 60, 111, 115, 116]. Its adaptation to novel environments may lead to increased vectorial capacity and survival, as well as greater risk of malaria transmission [117, 118]. The most likely drivers of Ny. darlingi divergence at a macro-geographic scale, across its broad distribution, are biogeographic or geographic boundaries and Pleistocene environmental changes [113, 119]. At a regional scale, isolation-by-distance has been shown to influence population structure [120], whereas at a micro-geographic scale, current local environmental conditions have a marked effect [113, 119, 120, 121, 122].

In Colombia, Ny. darlingi is distributed on either side of the Andes mountain range in lowland regions characterized by biogeographical and ecological heterogeneity [111]. West of the Andes, in the Urabá-Bajo Cauca and Alto Sinú (UCS) region, Ny. darlingi is the most common Nyssorhynchus species, exhibits endo and exophagy, is infected with P. vivax, and maintains transmission even at low abundance [60, 87, 111]. In most localities included in this study, the peak biting activity of Ny. darlingi was after 20:00 or 21:00 h when people conduct indoor and/or outdoor activities increasing the risk of vector-human contact. East of the Andes [111] and in southern Colombia, peak biting activity is at sunset [92] when no one is protected under ITNs. The dominance of Ny. darlingi in most of northwestern Colombian localities seems to be favored by ecological perturbations resulting from various human activities, such as alluvial mining, livestock, small-scale rice production, and forest fragment landscapes [60]. Vector control strategies that include ITNs are recommended for containment of Ny. darlingi populations [60, 87, 111, 123].

Studies on the genetic structure of Ny. darlingi in Colombia have shown that at the micro-geographic scale, in northwestern Colombia, Ny. darlingi is characterized by low genetic differentiation and high gene flow [123, 124]. The environmental heterogeneity that is a hallmark of this malaria endemic region does not reach a threshold to impact the population structure of Ny. darlingi [124]. A comprehensive genetic study that evaluated Ny. darlingi throughout its distribution in Colombia found that at a macro-geographic scale, differentiation into two main groups, west and east of the Andes, was most likely influenced by the Andes; at a micro-geographic scale, differentiation was partly the result of isolation by resistance, probably due to ecological differences, with significant impact on its population structure. In the current malaria scenario in Colombia and considering that Anophelinae mosquitoes adapt to climate and environmental changes, population studies should contribute to the development and implementation of vector control interventions and monitor their effectiveness in important malaria endemic regions of Colombia where Ny. darlingi maintains transmission.

Within Peru, only in the peri-Iquitos region of Loreto Department has the genetic structure of Ny. darlingi been evaluated, initially using Random Amplified Polymorphic DNA-PCR, that detected substantial homogeneity [125]. When populations from highway and riverine habitats were compared over a decade later using microsatellite markers, two highly admixed subpopulations were detected in each of nine villages [35]. The second major finding was that the 2012–2014 population of Ny. darlingi [35] had replaced that of the 2006 [126] and both of these subpopulations had the signature of a recent expansion. The source of the replacement population is unknown, although a broad analysis of microsatellite data across South America suggests that it most likely comes from western Brazil [35].

In Venezuela, Ny. darlingi is found in the lowland tropical rainforest, in the southern part of the country (Amazonas and Bolivar States), the piedmont ecoregion characterized by high rainfall and tropical forests in Trujillo State, western Venezuela, and in the llanos in central-western Venezuela, a subregion of the savanna ecoregion [127]. There is very little population structure in Venezuelan Ny. darlingi based on isozymes, RAPDs, ITS2 sequences [86], but more sensitive molecular markers, or whole genomes, might detect micro-geographic differences among the diverse ecoregions.

3.2. Nyssorhynchus albimanus

Nyssorhynchus albimanus is a malaria vector [27] characterized by ecological adaptability and a widespread, mostly coastal lowland, Neotropical distribution (Figure 4) [128]. Its presence usually coincides with areas that experience two annual rainy seasons, precipitation greater than 1000 mm, high relative humidity and a monthly variation in temperature between 22° and 29°C [127, 129, 130]. Despite its absence in Brazil, in Colombia, Ny. albimanus constitutes one of the main vectors in rural and peri-urban areas below 400–500 m, predominating along the Colombian Caribbean and Pacific Coasts and on the Island of San Andres [130, 131, 132, 133]. These regions have different levels of Plasmodium transmission and the importance of Ny. albimanus also differs [133]. The Pacific is a humid tropical forest and one of the rainiest regions globally; in contrast, the Caribbean tropical forest is drier and hotter [134]. Malaria cases increase in relation to ENSO patterns and cycles, particularly those transmitted by Ny. albimanus along the Pacific Coast of Colombia [61].

Figure 4.

Distribution of Nyssorhynchus albimanus (denoted by white dots). Map made in Google Earth Pro [83] using data from the Malaria Atlas Project [84, 85].

The availability of suitable breeding sites determines distribution and abundance of Ny. albimanus [130], a species that can thrive in fresh and brackish water, natural habitats (animal tracks, lakes, streams, and wells), and anthropogenic ones (rice fields, lagoons, and mining excavations, among others) [130, 135]. Behaviorally, Ny. albimanus is mainly zoophilic, exophagic, and exophilic; yet it can be anthropophilic, depending on local circumstances and abundance [130]. It is also known to be endophagic in local malaria hot-spots along the Pacific Coast, i.e., the urban sector of Buenaventura. The main outdoor biting time is 19:00–23:00 h, when many inhabitants are outside, and therefore exposed to biting and Plasmodium transmission [130]. As a vector of P. falciparum and P. vivax, Ny. albimanus has been incriminated in the Pacific region [133] and a new species from the southern Pacific Coast, Ny. albimanus B, detected by mitochondrial COI sequences, was infected with P. falciparum [57]. Despite the high abundance of Ny. albimanus in the Caribbean region, no infected specimens were detected [136].

Population genetic studies of Ny. albimanus in Colombia confirm its status of a single taxon throughout its distribution, with low population structuring and little genetic differentiation [137]. Two broader studies that included samples from Nicaragua to Ecuador, both nuclear and mitochondrial markers, found evidence for geographic structuring [138] and population contraction across Panama followed by an east-west expansion [139]. Under the hypothesis that malaria vectors are exposed to control pressures and environmental alterations that may lead to genotypic and phenotypic variation, genetic (microsatellite) and phenotypic (wing trait) data in populations of Ny. albimanus from the Pacific and Caribbean, despite a significant effect of environmental factors on wing traits, support a regional metapopulation of Ny. albimanus [132].

In Peru, Ny. albimanus is restricted to the Tumbes region of the northern coast, where it transmits P. vivax at the end of the hot rainy season. Local insecticide application, mostly in rice fields, lead to extreme levels of insecticide resistance [23]. A series of meetings and decisions between southern Ecuador and northern Peru health personnel resulted in a highly successful control program that employed a wide array of interventions such that autochthonous malaria was eliminated in El Oro, Ecuador in 2011 and in Tumbes, Peru in 2012 [135].

In Venezuela, Ny. albimanus is distributed along the coast and the margins of Valencia Lake, south of Maracay, although it does not appear to contribute to malaria transmission locally [127, 140]. It was found to be as abundant as the known coastal vector Ny. aquasalis in Aragua State, northcentral Venezuela, where both species had similar peak biting times during the early evening and were collected biting outdoors [141].

3.3. Nyssorhynchus albitarsis s.l.

The Albitarsis Complex comprises at least eight species [142] that extend across Central and South America and some Caribbean islands (Figure 5). The difficulty of their morphological differentiation complicates recognition of their role(s) in malaria transmission, an important aspect for the implementation of targeted and effective vector control strategies [143]. Three species are known vectors: Ny. deaneorum, Ny. janconnae, and Ny. marajoara. The latter is important regionally in Plasmodium transmission in central and eastern Brazil, where its distribution includes Amapá, Mato Grosso, Pará, and Rôndonia [84, 142]. Its role in transmission rivals that of Ny. darlingi in some habitat types such as peri-urban Macapá City, Amapá [144] and along the Rio Matapi, Amapá [88]. An entomological survey during an outbreak in western French Guiana, in an illegal gold mining area, detected a high P. vivax infectivity rate (6.4%) in specimens of Ny. marajoara [99]. An ecological niche model, based on current and future (2070), distributions of P. falciparum, Ny. darlingi, all species of the Albitarsis Complex, climate, biome and topography, projected that, whereas climate change would reduce suitable habitat for Ny. darlingi, both Ny. marajoara and Ny. deaneorum are expected to expand southward, thereby increasing their likely role in P. falciparum transmission by the projected date of 2070 [19].

Figure 5.

Distribution of the Albitarsis Complex (denoted by white dots). Map made in Google Earth Pro [83] using data from the Malaria Atlas Project [84, 85].

In Colombia, only a few species, in particular Ny. marajoara, have been identified morphologically in this complex [90, 145, 146, 147] and implicated in urban transmission [145]. This species is thought to be widespread in this country [110]. However, a detailed analysis of many Colombian specimens, identified molecularly, did not detect any individual Ny. marajoara [147], in agreement with Ruiz-Lopez et al. [142], whose study indicated that Ny. marajoara is restricted to the central-eastern and western regions of Brazil and is most likely absent in Colombia. Further studies need to be done on this vector to better frame its geographic distribution.

Albitarsis Complex species appear to be uncommon in Peru but this could reflect a general lack of Nyssorhynchus taxon sampling and molecular identification, particularly outside the Amazon region of Loreto.

Although there are several published reports of Ny. marajoara as an important regional malaria vector in Bolivar State, Venezuela, along with Ny. darlingi [77, 78, 148], a different species, Ny. albitarsis F in the Albitarsis Complex [142], was identified from the Caura Basin, Bolivar State [96]. In the most recent publication from the malaria hot-spot Sifontes, the specimens infected by Plasmodium are referred to only as Ny. albitarsis s.l. [80]. Hopefully, the correct species identities and distribution will soon be determined in this very crucial Venezuelan hot-spot.

3.4. The Nuneztovari Complex

The Nuneztovari Complex, extending through much of northern South America, includes Ny. nuneztovari (Figure 6), Nyssorhynchus dunhami, and Nyssorhynchus goeldii [149]. Like the Albitarsis Complex, species in the Nuneztovari Complex are similar morphologically and difficult to identify accurately. Scarpassa and collaborators [150] presented strong molecular evidence that additional species exist in Brazil and briefly reviewed the role of Ny. nuneztovari as a malaria vector in five Amazonian States. Nyssorhynchus nuneztovari is restricted to Colombia and western Venezuela, Ny. goeldii to Amazonian Brazil, and Ny. dunhami to central-western Brazil, Colombia and Amazonian Peru [71, 150]. It is difficult to evaluate the identification of these species in earlier publications, because distributions of Ny. nuneztovari and Ny. goeldii overlap, as do those of Ny. goeldii and Ny. dunhami [149, 150].

Figure 6.

Distribution of the Nuneztovari Complex (denoted by white dots). Map made in Google Earth Pro [83] using data from the Malaria Atlas Project [84, 85].

In Colombia, Ny. nuneztovari is an important malaria vector on both sides of the Andes presenting morphological, behavioral, and genetic heterogeneity throughout the country [151, 152]. In northwestern Colombia, it was found to be the most prevalent species, confirming an earlier study [58], and showed endo and exophagic behavior [152]. It was naturally infected by P. vivax VK247 [60, 87], positive for P. vivax VK210, and VK247 in the Pacific Coast [103]. In eastern Colombia, there are no recent reports of Ny. nuneztovari infected with Plasmodium, but more importantly, there is a lack of investigation of malaria outbreaks along the frontier with Venezuela with no record of species identification and vector incrimination. Because of the humanitarian crisis in Venezuela, the numbers of malaria cases have increased dramatically since 2010 [1, 153]. In the most recent study of Colombian Ny. nuneztovari, it was reported to be abundant and dominant in localities where anthropogenic activities such as livestock, fish-farming, and small to medium-scale agriculture were common, attributed to its adaptability to environmentally impacted habitats [152]. Common larval habitats were artificial fishponds and wetlands, particularly in the west and northwest [58, 152].

Regionally, this species shows the highest biting activity after 20:00 h, which suggests high transmission risk when people are at home, but not necessarily under nets. ITNs could be one component of an effective vector control intervention. In a locality in the northeast, Tibú, contiguous with Venezuela, peak biting of Ny. nuneztovari was after 21:00 h. This population differed genetically from other Colombian populations and its behavior was similar to Ny. nuneztovari from Venezuela. The populations exhibited endo and exophagic behavior in all localities and the results of the study indicated that region-specific interventions on both sides of the Andes would be most effective [152]. EIR values detected for Colombian Ny. nuneztovari were 3.5–3.6 in the northwest and 7.2 in the west. The highest value was in Buenaventura, on the Pacific Coast, where Ny. albimanus is considered the primary vector [133], but, according to the new study, Ny. nuneztovari also has a role in transmission in peri-urban Buenaventura [152].

In Peru, Ny. nuneztovari has been detected in five Departments: Pasco, Junín, Loreto, Ucayali, and Madre de Dios [154] and its presence confirmed in Loreto [155]. It may have a role in local malaria transmission, but remains unexplored. Nyssorhynchus nuneztovari is known as an important regional vector in western Venezuela where it occurs in seven States [156]. It was first identified morphologically in Bolivar State by Moreno et al. [157], from the malaria hot-spot of Sifontes municipality and was found infected by P. vivax (0.52%) [80]. It has also been found to be as abundant as Ny. darlingi in the Lower Caura River Basin, Bolivar State, where it was mostly active at sunset, although biting also throughout the night. Nevertheless, it was not detected infected by Plasmodium (although Ny. darlingi was), so the latter is more important in relation to malaria risk in the Caura River area [96].

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4. Conclusions and recommendations

As discussed by Packard [37], for sustainable malaria control, focusing on decreasing incidence towards elimination, effective measures need to be considered, including those related to human ecology. Examples include a significant improvement in living and housing conditions, redesigning of anthropogenic landscapes from those that favor mosquito vectors to a remodeled landscape that is both adequate for humans and inadequate for vector mosquitoes. The sustainability and success of a malaria control program depends on a combination of diagnosis of human infection, treatment with anti-malarial drugs, and vector control. Moreover, proposed changes will need to be maintained such that the malaria baseline will not be affected by either interruption or disruption of a control program [1]. It would be sensible to include malaria control in the One Health Program, to align it with the elimination of extreme poverty, a goal of the global sustainable development program.

The recent elimination of malaria on the Peru-Ecuador border was a successful strategy and included strengthening surveillance and treatment, resource sharing, the use of operational research to inform policy, and novel interventions [135]. The current program depends on prompt, effective diagnosis and treatment with no charge, community personnel trained to collect blood smears from febrile persons within their communities, case reporting to a national surveillance system that includes a five-category case definition (indigenous, imported, introduced, induced, and cryptic), active foci and case investigations, mapping and elimination of larval habitats, and the use of ITNs and LLINs. This could serve as a model for the current situation along the Venezuelan border with its neighbors, Colombia and Brazil. One very important aspect of this program is that it took 20 years to achieve its goals [135].

Worldwide, some of the innovations adopted for prevention, control, and eventual elimination of malaria transmission during the past ~10 years have included the development and deployment of LLINs [158, 159], the completion and exploration of many mosquito and parasite genomes [160, 161, 162, 163], major progress on genome editing in vector mosquitoes [164, 165, 166], new interventions such as house eaves [167] and push-pull systems [168], and better evaluation of larval source management (LSM) as a potential component of integrated control management systems [169]. Global policies and recommendations provide a useful framework and roadmap guided by the Global Technical Strategy of Malaria Control and Elimination (2016–2025), a reconsideration of the vectorial capacity formula for elimination [170] and the Plan for Elimination of Malaria in Brazil (UN/OMS 2015; [4]).

During the same 10-year timeframe, several novel tools and strategies have been envisaged that focus on the Neotropical malaria control and eradication landscape: (1) successful colonization of the main malaria vector Ny. darlingi [171, 172]; (2) development of predictive models on climate change scenarios for Neotropical malaria vectors and Plasmodium [18, 19]; and (3) collection of baseline larval habitat characteristics in malaria endemic regions that can guide larval source reduction [29, 48, 58, 173] and may prove effective as part of a broader array of vector interventions in certain landscape types such as abandoned gold mining pools [174] and possibly commercial fish ponds [31].

The most serious challenge to malaria eradication in South America from the viewpoint of vector control is that most vector species are primarily exophilic, often exophagic, and frequently bite early in the evening. Therefore, it is essential to determine and monitor the local biting behavior of a mosquito vector species.

Identified gaps in vector interventions throughout South American endemic areas are:

  1. Sustained funding for vector surveillance and intervention;

  2. Ongoing training programs for vector biologists and promoting community participation;

  3. Use of species distribution models to map potential distribution and epidemiology to focus interventions and planning;

  4. New efforts to control exophagic vectors and targeting aquatic stages should be part of integrated control and elimination programs that prioritize hot-spots;

  5. More accurate and timely identification of transmission in hot-spots;

  6. Routine evaluation of application strategies and insecticide resistance.

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Acknowledgments

We thank Sara Bickersmith, New York State Department of Health, Albany, NY, USA and Catharine Prussing, Department of Biomedical Sciences, State University of New York-Albany, NY, USA for creating the maps. Financial support was provided by US National Institutes of Health (NIH) NIH grant R01 AI110112 to JEC and ICEMR grant U19 AI089681 to J.M. Vinetz, COLCIENCIAS Colombia (Project code No. 596-2013) and Estrategia para la Sostenibilidad de Grupos de Investigación 2016–2107, Universidad de Antioquia, code No. ES84160123 to MMC, and FAPESP Grant no. 2014/26229-7 to MAMS. MEG thanks the Council for International Exchange of Scholars (US Department of State) for a Fulbright Scholar Fellowship to visit the Wadsworth Center, NYS Department of Health, Albany, NY, USA.

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Conflict of interest

The authors declare no conflict of interest.

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List of abbreviations

ACTartemisinin-based combination therapy
APIannual parasite index
COIcytochrome c oxidase I
DDTdichlorodiphenyltrichloroethane
EIRentomological inoculation rate
ELISAenzyme-linked immunosorbent assay
ENSOEl Niño-Southern oscillation
HBIhuman blood index
IRinfection rate
IRSindoor residual spraying
ITNinsecticide-treated net
ITS2internal transcribed spacer 2
LLINlong-lasting insecticide-treated net
LSMlarval source management
MOHMinistry of Health
PAHOPan American Health Organization
PCRpolymerase chain reaction
RAPDrandom amplified polymorphic DNA
WHOWorld Health Organization

References

  1. 1. WHO. World Malaria Report 2017. Geneva. Switzerland: World Health Organization; 2017
  2. 2. Recht J, Siqueira AM, Monteiro WM, Herrera SM, Herrera S, Lacerda MVG. Malaria in Brazil, Colombia, Peru and Venezuela: Current challenges in malaria control and elimination. Malaria Journal. 2017;16(1):273
  3. 3. Flores W, Chang J, Barillas E. Rapid assessment of the performance of malaria control strategies implemented by countries in the Amazon subregion using adequacy criteria: Case study. Malaria Journal. 2011;10:379
  4. 4. Ferreira MU, Castro MC. Challenges for malaria elimination in Brazil. Malaria Journal. 2016;15(1):284
  5. 5. Alonso P, Noor AM. The global fight against malaria is at crossroads. Lancet. 2017;390(10112):2532-2534
  6. 6. Grillet ME, Villegas L, Oletta JF, Tami A, Conn JE. Malaria in Venezuela requires response. Science. 2018 Feb 2;359(6375):528. PubMed PMID: 29420282. Epub 2018/02/09. eng
  7. 7. WHO. World Malaria Report 2015, Geneva. Switzerland: World Health Organization; 2015
  8. 8. Hiwat H, Mitro S, Samjhawan A, Sardjoe P, Soekhoe T, Takken W. Collapse of Anopheles darlingi populations in Suriname after introduction of insecticide-treated nets (ITNs); malaria down to near elimination level. The American Journal of Tropical Medicine and Hygiene. 2012;86(4):649-655
  9. 9. Grillet ME, Barrera R, Martinez JE, Berti J, Fortin MJ. Disentangling the effect of local and global spatial variation on a mosquito-borne infection in a neotropical heterogeneous environment. The American Journal of Tropical Medicine and Hygiene. 2010;82(2):194-201
  10. 10. da Silva-Nunes M, Moreno M, Conn JE, Gamboa D, Abeles S, Vinetz JM, et al. Amazonian malaria: Asymptomatic human reservoirs, diagnostic challenges, environmentally driven changes in mosquito vector populations, and the mandate for sustainable control strategies. Acta Tropica. 2012;121:281-291
  11. 11. Soto-Calle V, Rosas-Aguirre A, Llanos-Cuentas A, Abatih E, DeDeken R, Rodriguez H, et al. Spatio-temporal analysis of malaria incidence in the Peruvian Amazon region between 2002 and 2013. Scientific Reports. 2017;7:40350
  12. 12. Padilla JC, Uribe GÁ, Araújo RM, Narváez PC, Valencia SH. Epidemiology and control of malaria in Colombia. Memórias do Instituto Oswaldo Cruz. 2011;106(Suppl 1):14-22
  13. 13. Siqueira AM, Mesones-Lapouble O, Marchesini P, Sampaio VS, Brasil P, Tauil PL, et al. Plasmodium vivax landscape in Brazil: Scenario and challenges. The American Journal of Tropical Medicine and Hygiene. 2016;95(6 Suppl):87-96
  14. 14. Molina Gomez K, Caicedo MA, Gaitan A, Herrera-Varela M, Arce MI, Vallejo AF, et al. Characterizing the malaria rural-to-urban transmission interface: The importance of reactive case detection. PLoS Neglected Tropical Diseases. 2017;11(7):e0005780
  15. 15. Rovira-Vallbona E, Contreras-Mancilla JJ, Ramirez R, Guzmán-Guzmán M, Carrasco-Escobar G, Llanos-Cuentas A, et al. Predominance of asymptomatic and sub-microscopic infections characterizes the Plasmodium gametocyte reservoir in the Peruvian Amazon. PLoS Neglected Tropical Diseases. 2017;11(7):e0005674
  16. 16. Poveda G, Rojas W, Quinones ML, Velez ID, Mantilla RI, Ruiz D, et al. Coupling between annual and ENSO timescales in the malaria-climate association in Colombia. Environmental Health Perspectives. 2001;109(5):489-493
  17. 17. Grillet ME, El Souki M, Laguna F, Leon JR. The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela. Acta Tropica. 2014;129:52-60
  18. 18. Alimi TO, Fuller DO, Qualls WA, Herrera SV, Arevalo-Herrera M, Quinones ML, et al. Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population. Parasites & Vectors. 2015;8:431
  19. 19. Laporta GZ, Linton YM, Wilkerson RC, Bergo ES, Nagaki SS, Sant'Ana DC, et al. Malaria vectors in South America: Current and future scenarios. Parasites & Vectors. 2015;8:426
  20. 20. de Santana Filho FS, Arcanjo AR, Chehuan YM, Costa MR, Martinez-Espinosa FE, Vieira JL, et al. Chloroquine-resistant Plasmodium vivax, Brazilian Amazon. Emerging Infectious Diseases. 2007;13(7):1125-1126
  21. 21. Price RN, von Seidlein L, Valecha N, Nosten F, Baird JK, White NJ. Global extent of chloroquine-resistant Plasmodium vivax: A systematic review and meta-analysis. The Lancet Infectious Diseases. 2014;14(10):982-991
  22. 22. Marques MM, Costa MR, Santana Filho FS, Vieira JL, Nascimento MT, Brasil LW, et al. Plasmodium vivax chloroquine resistance and anemia in the western Brazilian Amazon. Antimicrobial Agents and Chemotherapy. 2014;58(1):342-347
  23. 23. Quinones ML, Norris DE, Conn JE, Moreno M, Burkot TR, Bugoro H, et al. Insecticide resistance in areas under investigation by the international centers of excellence for malaria research: A challenge for malaria control and elimination. The American Journal of Tropical Medicine and Hygiene. 2015;93(3 Suppl):69-78
  24. 24. Galardo AK, Povoa MM, Sucupira IM, Galardo CD, Santos RL. Anopheles darlingi and Anopheles marajoara (Diptera: Culicidae) susceptibility to pyrethroids in an endemic area of the Brazilian Amazon. Revista da Sociedade Brasileira de Medicina Tropical. 2015;48(6):765-769
  25. 25. Rosas-Aguirre A, Guzman-Guzman M, Gamboa D, Chuquiyauri R, Ramirez R, Manrique P, et al. Micro-heterogeneity of malaria transmission in the Peruvian Amazon: A baseline assessment underlying a population-based cohort study. Malaria Journal. 2017;16(1):312
  26. 26. Castellanos A, Chaparro-Narváez P, Morales-Plaza CD, Alzate A, Padilla J, Arévalo M, et al. Malaria in gold-mining areas in Colombia. Memórias do Instituto Oswaldo Cruz. 2016;111:59-66
  27. 27. Foster PG, de Oliveira TMP, Bergo ES, Conn JE, Sant'Ana DC, Nagaki SS, et al. Phylogeny of Anophelinae using mitochondrial protein coding genes. Royal Society Open Science. 2017 Nov;4(11):170758
  28. 28. Hiwat H, Bretas G. Ecology of Anopheles darlingi root with respect to vector importance: A review. Parasites & Vectors. 2011;4:177
  29. 29. Vittor AY, Pan W, Gilman RH, Tielsch J, Glass G, Shields T, et al. Linking deforestation to malaria in the Amazon: Characterization of the breeding habitat of the principal malaria vector, Anopheles darlingi. The American Journal of Tropical Medicine and Hygiene. 2009;81:5-12
  30. 30. de Barros FS, Tadei WP, Arruda ME, Honorio NA. On the use of classic epidemiological formulae for estimating the intensity of endemic malaria transmission by vectors in the Amazon. Neotropical Entomology. 2012;41(5):426-434
  31. 31. dos Reis IC, Honorio NA, Barros FS, Barcellos C, Kitron U, Camara DC, et al. Epidemic and endemic malaria transmission related to fish farming ponds in the Amazon frontier. PLoS One. 2015;10(9):e0137521
  32. 32. Perkins TA, Garcia AJ, Paz-Soldan VA, Stoddard ST, Reiner RC, Vazquez-Prokopec G, et al. Theory and data for simulating fine-scale human movement in an urban environment. Journal of the Royal Society, Interface. 2014;11(99):1-2. Article Number: 20140642
  33. 33. Carrasco-Escobar G, Gamboa D, Castro MC, Bangdiwala SI, Rodriguez H, Contreras-Mancilla J, et al. Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis. Scientific Reports. 2017;7(1):8082
  34. 34. Angelo JR, Katsuragawa TH, Sabroza PC, de Carvalho LA, Silva LH, Nobre CA. The role of spatial mobility in malaria transmission in the Brazilian Amazon: The case of Porto Velho municipality, Rondonia, Brazil (2010-2012). PLoS One. 2017;12(2):e0172330
  35. 35. Lainhart W, Bickersmith S, Nadler K, Moreno M, Saavedra M, Chu VM, et al. Evidence for temporal population replacement and the signature of ecological adaptation in a major Neotropical malaria vector in Amazonian Peru. Malaria Journal. 2015;14(1):375
  36. 36. Tucker Lima JM, Vittor A, Rifai S, Valle D. Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 2017;372(1722)
  37. 37. Packard RM. The making of a tropical disease: A short history of malaria. Emerging Infectious Diseases. 2008;14(10):1679
  38. 38. WHO. World Malaria Report 2016. Geneva: World Health Organization; 2016
  39. 39. Kohara Melchior LA, Chiaravalloti Neto F. Spatial and spatio-temporal analysis of malaria in the state of acre, western Amazon, Brazil. Geospatial Health. 2016;11(3):443
  40. 40. Lana RM, Riback TIS, Lima TFM, da Silva-Nunes M, Cruz OG, Oliveira FGS, et al. Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis. Malaria Journal. 2017;16(1):397
  41. 41. Pan American Health Organization. Report on the Situation of Malaria in the Americas, 2000-2015. 2017
  42. 42. Ministério da Saúde. Boletim Malária Região Amazônica. www.saude.gov.br/malaria: Ministério da Saúde; 2018 [cited 2018 Jan 4]
  43. 43. Instituto Nacional de Salud (INS). Instituto Nacional de Salud, Boletín epidemiológico Semanal. Estadísticas del sistema de vigilancia en salud pública- SIVIGILA, Casos totales en la Semana Epidemiológica 52 y acumulados del año, Subdirección de Vigilancia y Control en Salud Pública. Bogotá: Instituto Nacional de Salud; 2017
  44. 44. Ministerio de Salud. Centro Nacional de Epidemiologia, Prevención y Control de Enfermedades—MINSA (*) Hasta la SE 51 del 2017. Lima, Peru: Ministerio de Salud Perú; 2017
  45. 45. Ministerio del Poder Popular para la Salud (MPPS). Ministerio del Poder Popular para la Salud. Caracas, Venezuela. 2018. http://www.vicepresidencia.gob.ve/index.php/tag/ministerio-del-poder-popular-para-la-salud/ [cited January 5 2018]
  46. 46. Lima ID, Lapouble OM, Duarte EC. Time trends and changes in the distribution of malaria cases in the Brazilian Amazon region, 2004-2013. Memórias do Instituto Oswaldo Cruz. 2017;112(1):8-18
  47. 47. Manguin S, Roberts DR, Andre RG, Rejmankova E, Hakre S. Characterization of Anopheles darlingi (Diptera: Culicidae) larval habitats in Belize, Central America. Journal of Medical Entomology. 1996 Mar;33(2):205-211. PubMed PMID: 8742522. Epub 1996/03/01. eng
  48. 48. Rufalco-Moutinho P, Schweigmann N, Bergamaschi DP, Mureb Sallum MA. Larval habitats of Anopheles species in a rural settlement on the malaria frontier of Southwest Amazon, Brazil. Acta Tropica. 2016;164:243-258
  49. 49. Vitor-Silva S, Siqueira AM, de Souza Sampaio V, Guinovart C, Reyes-Lecca RC, de Melo GC, et al. Declining malaria transmission in rural Amazon: Changing epidemiology and challenges to achieve elimination. Malaria Journal. 2016;15(1):266
  50. 50. Braz RM, Duarte EC, Tauil PL. Characteristics of malaria epidemics in the municipalities of the Brazilian Amazon, 2010. Cadernos de Saúde Pública. 2013;29(5):935-944. Caracterizacao das epidemias de malaria nos municipios da Amazonia Brasileira em 2010
  51. 51. Instituto Nacional de Salud (INS). Boletín epidemiológico Semanal. Estadísticas del sistema de vigilancia en salud pública- SIVIGILA, Casos totales en la Semana Epidemiológica 52 y acumulados del año, Subdirección de Vigilancia y Control en Salud Pública. 2015. 2015
  52. 52. Instituto Nacional de Salud (INS). Instituto Nacional de Salud, Boletín epidemiológico Semanal. Estadísticas del sistema de vigilancia en salud pública- SIVIGILA, Casos totales en la Semana Epidemiológica 52 y acumulados del año, Subdirección de Vigilancia y Control en Salud Pública. 2016
  53. 53. Padilla JC, Chaparro PE, Molina K, Arevalo-Herrera M, Herrera S. Is there malaria transmission in urban settings in Colombia? Malaria Journal. 2015;14:453
  54. 54. Colombian Malaria Project. Colombian Malaria Project report—years 4 and 5, 2013-2014 [web]. Bogotá 2017 [cited Nov 2017]. Available from: http://www.ins.gov.co/temas-de-interes/Paginas/memorias.aspx
  55. 55. Gomez GF, Correa MM. Discrimination of Neotropical Anopheles species based on molecular and wing geometric morphometric traits. Infection, Genetics and Evolution. 2017;54:379-386
  56. 56. Lopez-Rubio A, Suaza-Vasco J, Marcet PL, Ruiz-Molina N, Caceres L, Porter C, et al. Use of DNA barcoding to distinguish the malaria vector Anopheles neivai in Colombia. Zootaxa. 2016;4175(4):377-389
  57. 57. Ahumada ML, Orjuela LI, Pareja PX, Conde M, Cabarcas DM, Cubillos EF, et al. Spatial distributions of Anopheles species in relation to malaria incidence at 70 localities in the highly endemic Northwest and South Pacific Coast regions of Colombia. Malaria Journal. 2016;15(1):407
  58. 58. Conde M, Pareja PX, Orjuela LI, Ahumada ML, Duran S, Jara JA, et al. Larval habitat characteristics of the main malaria vectors in the most endemic regions of Colombia: Potential implications for larval control. Malaria Journal. 2015;14(1):476
  59. 59. Jiménez IP, Conn J, Brochero H. Preliminary biological studies on larvae and adult Anopheles mosquitoes (Diptera: Culicidae) in Miraflores, a malaria endemic locality in Guaviare department, Amazonian Colombia. Journal of Medical Entomology. 2014;51(5):1002-1009
  60. 60. Naranjo-Diaz N, Rosero DA, Rua-Uribe G, Luckhart S, Correa MM. Abundance, behavior and entomological inoculation rates of anthropophilic anophelines from a primary Colombian malaria endemic area. Parasites & Vectors. 2013;6:61
  61. 61. Ruiz D, Ceron V, Molina AM, Quinones ML, Jimenez MM, Ahumada M, et al. Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: Description of study sites. The American Journal of Tropical Medicine and Hygiene. 2014;91(1):27-38
  62. 62. Rosas-Aguirre A, Gamboa D, Manrique P, Conn JE, Moreno M, Lescano AG, et al. Epidemiology of Plasmodium vivax malaria in Peru. The American Journal of Tropical Medicine and Hygiene. 2016;95(6 Suppl):133-144
  63. 63. Rosas-Aguirre A, Speybroeck N, Llanos-Cuentas A, Rosanas-Urgell A, Carrasco-Escobar G, Rodriguez H, et al. Hotspots of malaria transmission in the Peruvian Amazon: Rapid assessment through a parasitological and serological survey. PLoS One. 2015;10(9):e0137458
  64. 64. MINSA. Ministerio de Salud del Perú: Sala de Situación de Salud: Epidemiológica N° 52-2017. 2017
  65. 65. Sanchez JF, Carnero AM, Rivera E, Rosales LA, Baldeviano GC, Asencios JL, et al. Unstable malaria transmission in the southern Peruvian Amazon and its association with gold mining, Madre de Dios, 2001-2012. The American Journal of Tropical Medicine and Hygiene. 2017;96(2):304-311
  66. 66. Rosas-Aguirre A, Llanos-Cuentas A, Speybroeck N, Cook J, Contreras-Mancilla J, Soto V, et al. Assessing malaria transmission in a low endemicity area of North-Western Peru. Malaria Journal. 2013;12:339
  67. 67. MINSA. Ministerio de Salud del Perú. Tendenica y situación de las enfermedades sujetas a vigilancia epidemiológica: malaria. Boletin Epidemiologico. 2015;24:975-986
  68. 68. Quispe AM, Llanos-Cuentas A, Rodriguez H, Clendenes M, Cabezas C, Leon LM, et al. Accelerating to zero: Strategies to eliminate malaria in the Peruvian Amazon. The American Journal of Tropical Medicine and Hygiene. 2016;94(6):1200-1207
  69. 69. Instituto Nacional de Estadisticas e Informatica. Estimaciones y Proyecciones de Población Total por Sexo de las Principales Ciudades 2000-2015. Lima, Peru; 2012
  70. 70. Reinbold-Wasson DD, Sardelis MR, Jones JW, Watts DM, Fernandez R, Carbajal F, et al. Determinants of Anopheles seasonal distribution patterns across a forest to periurban gradient near Iquitos, Peru. The American Journal of Tropical Medicine and Hygiene. 2012;86(3):459-463
  71. 71. Moreno M, Saavedra MP, Bickersmith SA, Lainhart W, Tong C, Alava F, et al. Implications for changes in Anopheles darlingi biting behaviour in three communities in the peri-Iquitos region of Amazonian Peru. Malaria Journal. 2015;14:290
  72. 72. Chuquiyauri R, Paredes M, Penataro P, Torres S, Marin S, Tenorio A, et al. Socio-demographics and the development of malaria elimination strategies in the low transmission setting. Acta Tropica. 2012;121(3):292-302
  73. 73. Parker BS, Paredes Olortegui M, Penataro Yori P, Escobedo K, Florin D, Rengifo Pinedo S, et al. Hyperendemic malaria transmission in areas of occupation-related travel in the Peruvian Amazon. USA: Malaria Journal. 2013;12:178
  74. 74. Pan American Health Organization. Malaria in the Bolivarian Republic of Venezuela. Washington D.C., USA. 2017
  75. 75. Hotez PJ, Basanez MG, Acosta-Serrano A, Grillet ME. Venezuela and its rising vector-borne neglected diseases. PLoS Neglected Tropical Diseases. 2017;11(6):e0005423
  76. 76. Hotez PJ. Ten failings in global neglected tropical diseases control. PLoS Neglected Tropical Diseases. 2017;11(12):e0005896
  77. 77. Moreno JE, Rubio-Palis Y, Paez E, Perez E, Sanchez V. Abundance, biting behaviour and parous rate of anopheline mosquito species in relation to malaria incidence in gold-mining areas of southern Venezuela. Medical and Veterinary Entomology. 2007;21(4):339-349
  78. 78. Moreno JE, Rubio-Palis Y, Paez E, Perez E, Sanchez V, Vaccari E. Malaria entomological inoculation rates in gold mining areas of Southern Venezuela. Memórias do Instituto Oswaldo Cruz. 2009;104(5):764-768
  79. 79. Moreno JE, Rubio-Palis Y, Sanchez V, Martinez A. Caracterización de hábitats larvales de anofelinos en el municipio Sifontes del estado Bolívar, Venezuela. Boletin de Malariologia y Salud Ambiental LV. 2015;2:117-131
  80. 80. Orm SA, Moreno JE, Carrozza M, Acevedo P, Herrera F. Plasmodium spp. infection rates for some Anopheles spp. from Sifontes municipality, Bolívar State, Venezuela. Boletin de Malariologia y Salud Ambiental 2017;LVII(1):17-25
  81. 81. Casey N. Hard times in Venezuela breed malaria as desperate flock to mines. New York Times. 2016
  82. 82. Griffing SM, Villegas L, Udhayakumar V. Malaria control and elimination, Venezuela, 1800s -1970s. Emerging Infectious Diseases. 2014;20(10):1697-1704
  83. 83. Google Earth. Latin America: 4°59′43”S 66°33′57”W. Available from: https://earth.google.com/web: GOOGLE EARTH v 9.2.52.4; [Accessed: February 23, 2018]
  84. 84. Sinka ME, Rubio-Palis Y, Manguin S, Patil AP, Temperley WH, Gething PW, et al. The dominant Anopheles vectors of human malaria in the Americas: Occurrence data, distribution maps and bionomic precis. Parasites & Vectors. 2010 Aug 16;3:72. PubMed PMID: 20712879. Pubmed Central PMCID: Pmc2936890. Epub 2010/08/18. eng
  85. 85. Hay SI, Snow RW. The malaria atlas project: Developing global maps of malaria risk. PLoS Medicine. 2006;3(12):e473
  86. 86. Manguin S, Wilkerson RC, Conn JE, Rubio-Palis Y, Danoff-Burg JA, Roberts DR. Population structure of the primary malaria vector in South America, Anopheles darlingi, using isozyme, random amplified polymorphic DNA, internal transcribed spacer 2, and morphologic markers. The American Journal of Tropical Medicine and Hygiene. 1999;60(3):364-376
  87. 87. Gutierrez LA, Gonzalez JJ, Gomez GF, Castro MI, Rosero DA, Luckhart S, et al. Species composition and natural infectivity of anthropophilic Anopheles (Diptera: Culicidae) in the states of Cordoba and Antioquia, northwestern Colombia. Memórias do Instituto Oswaldo Cruz. 2009;104(8):1117-1124
  88. 88. Galardo AK, Arruda M, D'Almeida Couto AA, Wirtz R, Lounibos LP, Zimmerman RH. Malaria vector incrimination in three rural riverine villages in the Brazilian Amazon. The American Journal of Tropical Medicine and Hygiene. 2007;76(3):461-469
  89. 89. Martins-Campos KM, Pinheiro WD, Vitor-Silva S, Siqueira AM, Melo GC, Rodrigues IC, et al. Integrated vector management targeting Anopheles darlingi populations decreases malaria incidence in an unstable transmission area, in the rural Brazilian Amazon. Malaria Journal. 2012;11:351
  90. 90. Jimenez P, Conn JE, Wirtz R, Brochero H. Anopheles (Diptera: Culicidae) vectors of malaria in Puerto Carreno municipality, Vichada, Colombia. Biomedica. 2012;32(Suppl 1):13-21
  91. 91. Jiménez IP, Conn JE, Brochero H. Malaria Vectors in San José del Guaviare, Orinoquia, Colombia. Journal of the American Mosquito Control Association. 2014;30(2):91-98
  92. 92. Ahumada ML, Pareja PX, Buitrago LS, Quinones ML. Biting behavior of Anopheles darlingi root, 1926 (Diptera: Culicidae) and its association with malaria transmission in Villavicencio (Meta, Colombia). Biomédica. 2013;33(2):241-250
  93. 93. Dusfour I, Issaly J, Carinci R, Gaborit P, Girod R. Incrimination of Anopheles (Anopheles) intermedius Peryassu, An. (Nyssorhynchus) nuneztovari Gabaldon, An. (Nys.) oswaldoi Peryassu as natural vectors of Plasmodium falciparum in French Guiana. Memórias do Instituto Oswaldo Cruz. 2012 May;107(3):429-432
  94. 94. Hiwat H, Issaly J, Gaborit P, Somai A, Samjhawan A, Sardjoe P, et al. Behavioral heterogeneity of Anopheles darlingi (Diptera: Culicidae) and malaria transmission dynamics along the Maroni River, Suriname, French Guiana. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2010;104(3):207-213
  95. 95. Girod R, Roux E, Berger F, Stefani A, Gaborit P, Carinci R, et al. Unravelling the relationships between Anopheles darlingi (Diptera: Culicidae) densities, environmental factors and malaria incidence: Understanding the variable patterns of malarial transmission in French Guiana (South America). Annals of Tropical Medicine and Parasitology. 2011;105(2):107-122
  96. 96. Rubio-Palis Y, Bevilacqua M, Medina DA, Moreno JE, Cardenas L, Sanchez V, et al. Malaria entomological risk factors in relation to land cover in the lower Caura River basin, Venezuela. Memórias do Instituto Oswaldo Cruz. 2013 Apr;108(2):220-228
  97. 97. Moreno M, Saavedra MP, Bickersmith SA, Prussing C, Michalski A, Tong Rios C, et al. Intensive trapping of blood-fed Anopheles darlingi in Amazonian Peru reveals unexpectedly high proportions of avian blood-meals. PLoS Neglected Tropical Diseases. 2017;11(2):e0005337
  98. 98. Montoya C, Bascunan P, Rodriguez-Zabala J, Correa MM. Abundance, composition and natural infection of Anopheles mosquitoes from two malaria-endemic regions of Colombia. Biomédica. 2017;37:98-105
  99. 99. Pommier de Santi V, Girod R, Mura M, Dia A, Briolant S, Djossou F, et al. Epidemiological and entomological studies of a malaria outbreak among French armed forces deployed at illegal gold mining sites reveal new aspects of the disease's transmission in French Guiana. Malaria Journal. 2016;15:35
  100. 100. Vezenegho SB, Adde A, Pommier de Santi V, Issaly J, Carinci R, Gaborit P, et al. High malaria transmission in a forested malaria focus in French Guiana: How can exophagic Anopheles darlingi thwart vector control and prevention measures? Memórias do Instituto Oswaldo Cruz. 2016;111(9):561-569
  101. 101. Pommier de Santi V, Dusfour I, de Parseval E, Lespinet B, Nguyen C, Gaborit P, et al. Risk of daytime transmission of malaria in the French Guiana rain forest. Medecine et sante tropicales. 2017;27(1):111-112. Risque de transmission diurne du paludisme en foret guyanaise
  102. 102. Herrera-Varela M, Orjuela LI, Penalver C, Conn JE, Quinones ML. Anopheles species composition explains differences in Plasmodium transmission in La Guajira, northern Colombia. Memórias do Instituto Oswaldo Cruz. 2014;109(7):955-959
  103. 103. Naranjo-Diaz N, Altamiranda M, Luckhart S, Conn JE, Correa MM. Malaria vectors in ecologically heterogeneous localities of the Colombian Pacific region. PLoS One. 2014;9(8):e103769
  104. 104. Cohuet A, Harris C, Robert V, Fontenille D. Evolutionary forces on Anopheles: What makes a malaria vector? Trends in Parasitology. 2010;26(3):130-136
  105. 105. Kaufman MG, Fonseca DM. Invasion biology of Aedes japonicus japonicus (Diptera: Culicidae). Annual Review of Entomology. 2014;59:31-49
  106. 106. Lounibos LP, Kramer LD. Invasiveness of Aedes aegypti and Aedes albopictus and vectorial capacity for Chikungunya virus. The Journal of Infectious Diseases. 2016;214(suppl 5):S453-s458
  107. 107. Aramburu Guarda J, Ramal Asayag C, Witzig R. Malaria reemergence in the Peruvian Amazon region. Emerging Infectious Diseases. 1999;5(2):209-215
  108. 108. Schoeler GB, Flores-Mendoza C, Fernandez R, Davila JR, Zyzak M. Geographical distribution of Anopheles darlingi in the Amazon Basin region of Peru. Journal of the American Mosquito Control Association. 2003;19(4):286-296
  109. 109. Vittor AY, Gilman RH, Tielsch J, Glass G, Shields T, Lozano WS, et al. The effect of deforestation on the human-biting rate of Anopheles darlingi, the primary vector of falciparum malaria in the Peruvian Amazon. The American Journal of Tropical Medicine and Hygiene. 2006;74:3-11
  110. 110. Gonzalez R, Carrejo N. Introducción al estudio taxonómico de Anopheles de Colombia Claves y notas de distribución. 2nd ed. Cali; Programa Editorial Universidad de Valle; 2009. 260 pp. Epub 2
  111. 111. Naranjo-Diaz N, Conn JE, Correa MM. Behavior and population structure of Anopheles darlingi in Colombia. Infection, Genetics and Evolution. 2016;39:64-73
  112. 112. Pedro PM, Sallum MAM. Spatial expansion and population structure of the neotropical malaria vector, Anopheles darlingi (Diptera: Culicidae). Biological Journal of the Linnean Society. 2009;97(4):854-866
  113. 113. Emerson KJ, Conn JE, Bergo ES, Randel MA, Sallum MAM. Brazilian Anopheles darlingi (Diptera: Culicidae) clusters by major biogeographical region. PLoS One. 2015;10(7):e0130773
  114. 114. Zimmerman RH, Galardo AK, Lounibos LP, Arruda M, Wirtz R. Bloodmeal hosts of Anopheles species (Diptera: Culicidae) in a malaria-endemic area of the Brazilian Amazon. Journal of Medical Entomology. 2006;43(5):947-956
  115. 115. Rejmankova E, Rubio-Palis Y, Villegas L. Larval habitats of anopheline mosquitoes in the upper Orinoco, Venezuela. Journal of Vector Ecology. 1999;24(2):130-137
  116. 116. Gil LH, Tada MS, Katsuragawa TH, Ribolla PE, da Silva LH. Urban and suburban malaria in Rondonia (Brazilian western Amazon) II. Perennial transmissions with high anopheline densities are associated with human environmental changes. Memórias do Instituto Oswaldo Cruz. 2007;102(3):271-276
  117. 117. Moutinho PR, Gil LH, Cruz RB, Ribolla PE. Population dynamics, structure and behavior of Anopheles darlingi in a rural settlement in the Amazon rainforest of acre, Brazil. Malaria Journal. 2011;10:174
  118. 118. Conn JE, Ribolla PE. Ecology of Anopheles darlingi, the primary malaria vector in the Americas and current nongenetic methods of vector control. In: Adelman ZN, editor. Genetic Control of Malaria and Dengue. Oxford: Academic Press; 2015. pp. 81-102
  119. 119. Loaiza JR, Bermingham E, Sanjur OI, Scott ME, Bickersmith SA, Conn JE. Review of genetic diversity in malaria vectors (Culicidae: Anophelinae). Infection, Genetics and Evolution. 2012;12(1):1-12
  120. 120. Scarpassa VM, Conn JE. Population genetic structure of the major malaria vector Anopheles darlingi (Diptera: Culicidae) from the Brazilian Amazon, using microsatellite markers. Memórias do Instituto Oswaldo Cruz. 2007;102(3):319-327
  121. 121. Angella AF, Salgueiro P, Gil LH, Vicente JL, Pinto J, Ribolla PE. Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi. Malaria Journal. 2014;13:203
  122. 122. Campos M, Conn JE, Alonso DP, Vinetz JM, Emerson KJ, Ribolla PE. Microgeographical structure in the major Neotropical malaria vector Anopheles darlingi using microsatellites and SNP markers. Parasites & Vectors. 2017;10(1):76
  123. 123. Gutiérrez LA, Gomez GF, Gonzalez JJ, Castro MI, Luckhart S, Conn JE, et al. Microgeographic genetic variation of the malaria vector Anopheles darlingi root (Diptera: Culicidae) from Cordoba and Antioquia, Colombia. The American Journal of Tropical Medicine and Hygiene. 2010;83(1):38-47
  124. 124. Altamiranda-Saavedra M, Conn JE, Correa MM. Genetic structure and phenotypic variation of Anopheles darlingi in Northwest Colombia. Infection, Genetics and Evolution. 2017;56:143-151
  125. 125. Pinedo-Cancino V, Sheen P, Tarazona-Santos E, Oswald WE, Jeri C, Vittor AY, et al. Limited diversity of Anopheles darlingi in the Peruvian Amazon region of Iquitos. The American Journal of Tropical Medicine and Hygiene. 2006;75(2):238-245
  126. 126. Mirabello L, Vineis JH, Yanoviak SP, Scarpassa VM, Povoa MM, Padilla N, et al. Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in central and South America. BMC Ecology. 2008;8:3
  127. 127. Rubio-Palis Y, Zimmerman RH. Ecoregional classification of malaria vectors in the neotropics. Journal of Medical Entomology. 1997;34(5):499-510
  128. 128. Faran ME. Mosquito studies (Diptera, Culicidae) XXXIV. A revision of the Albimanus section of the subgenus Nyssorhynchus of Anopheles. Contributions of the American Entomological Institute. 1980;15:1-215
  129. 129. Loaiza JR, Scott ME, Bermingham E, Rovira J, Conn JE. Evidence for pleistocene population divergence and expansion of Anopheles albimanus in southern central America. The American Journal of Tropical Medicine and Hygiene. 2010;82(1):156-164
  130. 130. Montoya-Lerma J, Solarte YA, Giraldo-Calderon GI, Quinones ML, Ruiz-Lopez F, Wilkerson RC, et al. Malaria vector species in Colombia: A review. Memórias do Instituto Oswaldo Cruz. 2011;106(Suppl 1):223-238
  131. 131. Olano V, Brochero H, Sáenz R, Quiñones M, Molina J. Mapas preliminares de la distribución de especies de Anopheles vectores de malaria en Colombia. Biomédica. 2001;21:402-408
  132. 132. Gómez GF, Márquez EJ, Gutiérrez LA, Conn JE, Correa MM. Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation. Acta Tropica. 2014;135:75-85
  133. 133. Gutiérrez LA, Naranjo N, Jaramillo LM, Muskus C, Luckhart S, Conn JE, et al. Natural infectivity of Anopheles species from the Pacific and Atlantic regions of Colombia. Acta Tropica. 2008;107:99-105
  134. 134. Instituto Geografico Agustin Codazzi. Bogota: Atlas de Colombia; 2002:167. Epub 5. http://www2.igac.gov.co/igac_web/contenidos/plantilla_general_titulo_contenido.jsp?idMenu=328
  135. 135. Krisher LK, Krisher J, Ambuludi M, Arichabala A, Beltran-Ayala E, Navarrete P, et al. Successful malaria elimination in the Ecuador-Peru border region: Epidemiology and lessons learned. Malaria Journal. 2016;15(1):573
  136. 136. Cáceres DC, De La Hoz F, Nicholls S, DeAntonio R, Velandia MP, Olano V, et al. Brote de malaria en La Guajira, 1 de diciembre de 1999 a 1 de febrero de 2000. Biomédica. 2000;20:152-161
  137. 137. Gutiérrez LA, Naranjo NJ, Cienfuegos AV, Muskus CE, Luckhart S, Conn JE, et al. Population structure analyses and demographic history of the malaria vector Anopheles albimanus from the Caribbean and the Pacific regions of Colombia. Malaria Journal. 2009;8:259
  138. 138. Molina-Cruz A, de Merida AM, Mills K, Rodriguez F, Schoua C, Yurrita MM, et al. Gene flow among Anopheles albimanus populations in central America, South America, and the Caribbean assessed by microsatellites and mitochondrial DNA. The American Journal of Tropical Medicine and Hygiene. 2004 Sep;71(3):350-359. PubMed PMID: 15381818. Epub 2004/09/24. eng
  139. 139. Loaiza JR, Scott ME, Bermingham E, Sanjur OI, Wilkerson R, Rovira J, et al. Late Pleistocene environmental changes lead to unstable demography and population divergence of Anopheles albimanus in the northern Neotropics. Molecular Phylogenetics and Evolution. 2010;57(3):1341-1346
  140. 140. Lounibos LP, Conn JE. Malaria vector heterogeneity in South America. American Entomologist. 2000;46(4):238-249
  141. 141. Rubio-Palis Y. Evaluation of light traps combined with carbon dioxide and 1-octen-3-ol to collect anophelines in Venezuela. Journal of the American Mosquito Control Association. 1996 Mar;12(1):91-96. PubMed PMID: 8723264. Epub 1996/03/01. eng
  142. 142. Ruiz-Lopez F, Wilkerson RC, Conn JE, McKeon SN, Levin DM, Quinones ML, et al. DNA barcoding reveals both known and novel taxa in the Albitarsis group (Anopheles: Nyssorhynchus) of Neotropical malaria vectors. Parasites & Vectors. 2012;5:44
  143. 143. WHO. World Malaria Report 2012. Geneva: WHO; 2012
  144. 144. Conn JE, Wilkerson RC, Segura MN, de Souza RT, Schlichting CD, Wirtz RA, et al. Emergence of a new neotropical malaria vector facilitated by human migration and changes in land use. The American Journal of Tropical Medicine and Hygiene. 2002;66(1):18-22
  145. 145. Brochero HL, Rey G, Buitrago LS, Olano VA. Biting activity and breeding sites of Anopheles species in the municipality Villavicencio, meta, Colombia. Journal of the American Mosquito Control Association. 2005;21(2):182-186
  146. 146. Brochero HH, Li C, Wilkerson RC. A newly recognized species in the Anopheles (Nyssorhynchus) albitarsis complex (Diptera: Culicidae) from Puerto Carreno, Colombia. The American Journal of Tropical Medicine and Hygiene. 2007;76(6):1113-1117
  147. 147. Gomez G, Jaramillo L, Correa MM. Wing geometric morphometrics and molecular assessment of members in the Albitarsis complex from Colombia. Molecular Ecology Resources. 2013;13(6):1082-1092
  148. 148. Moreno JE, Rubio-Palis Y, Martinez AR, Acevedo P. Evolución espacial y temporal de la malaria en el municipio Sifontes del estado Bolívar, Venezuela. 1980-2013. Boletin de Malariologia y Salud Ambiental. 2014;54(2):236-249
  149. 149. Foster PG, Bergo ES, Bourke BP, Oliveira TM, Nagaki SS, Sant'Ana DC, et al. Phylogenetic analysis and DNA-based species confirmation in Anopheles (Nyssorhynchus). PLoS One. 2013;8(2):e54063
  150. 150. Scarpassa VM, Cunha-Machado AS, Saraiva JF. Evidence of new species for malaria vector Anopheles nuneztovari sensu lato in the Brazilian Amazon region. Malaria Journal. 2016;15:205
  151. 151. Gómez G, Cienfuegos A, Gutiérrez L, Conn J, Correa M. Análisis morfológico y molecular evidencia problemas al identificar Anopheles nuneztovari (Diptera: Culicidae) por claves dicotómicas. Revista Colombiana de Entomologia. 2010;36:68-75
  152. 152. Naranjo-Díaz N, Sallum MAM, Correa MM. Population dynamics of Anopheles nuneztovari in Colombia. Infection, genetics and evolution. Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases. 2016;45:56-65
  153. 153. Welle D. WHO: Cases of Malaria are Triggered in Venezuela and Colombia, for Different Reasons. 2017. Available from: www.dw.com: Deutsche Welle; http://p.dw.com/p/2oUld [Accessed: January 18, 2018]
  154. 154. Calderón G, Fernández R, Valle J. Especies de la fauna anofelina, su distribucion y algunas consideraciones sobre su abundancia e infectividad en el Peru. Revista Peruana de Epidemiología. 1995;8(1):5-23
  155. 155. Matson R, Rios CT, Chavez CB, Gilman RH, Florin D, Sifuentes VL, et al. Improved molecular technique for the differentiation of neotropical anopheline species. The American Journal of Tropical Medicine and Hygiene. 2008;78(3):492-498
  156. 156. Rubio-Palis Y. Anopheles (Nyssorhynchus) de Venezuela. Taxonomía, bionomía, ecología e importancia médica. Maracay, Venezuela: Publicaciones de la Dirección de Malariologia; 2000
  157. 157. Moreno JE, Rubio-Palis Y, Sanchez V, Mariany D. Primer registro de Anopheles (Nyssorhynchus) nuneztovari Gabaldón,1940 (Diptera: Culicidae) en el estado Bolívar, Venezuela y sus implicaciones eco-epidemiológicas. Entomotropica. 2004;19(1):55-58
  158. 158. Gatton ML, Chitnis N, Churcher T, Donnelly MJ, Ghani AC, Godfray HC, et al. The importance of mosquito behavioural adaptations to malaria control in Africa. Evolution. 2013;67(4):1218-1230
  159. 159. Koenker HM, Yukich JO, Mkindi A, Mandike R, Brown N, Kilian A, et al. Analysing and recommending options for maintaining universal coverage with long-lasting insecticidal nets: The case of Tanzania in 2011. Malaria Journal. 2013;12:150
  160. 160. Neafsey DE, Galinsky K, Jiang RH, Young L, Sykes SM, Saif S, et al. The malaria parasite Plasmodium vivax exhibits greater genetic diversity than Plasmodium falciparum. Nature Genetics. 2012;44(9):1046-1050
  161. 161. Neafsey DE, Waterhouse RM, Abai MR, Aganezov SS, Alekseyev MA, Allen JE, et al. Mosquito genomics. Highly evolvable malaria vectors: The genomes of 16 Anopheles mosquitoes. Science. 2015;347(6217):1258522
  162. 162. Love RR, Steele AM, Coulibaly MB, Traore SF, Emrich SJ, Fontaine MC, et al. Chromosomal inversions and ecotypic differentiation in Anopheles gambiae: The perspective from whole-genome sequencing. Molecular Ecology. 2016;25(23):5889-5906
  163. 163. Auburn S, Bohme U, Steinbiss S, Trimarsanto H, Hostetler J, Sanders M, et al. A new Plasmodium vivax reference sequence with improved assembly of the subtelomeres reveals an abundance of pir genes. Wellcome Open Research. 2016;1:4
  164. 164. Hammond A, Galizi R, Kyrou K, Simoni A, Siniscalchi C, Katsanos D, et al. A CRISPR-Cas9 gene drive system targeting female reproduction in the malaria mosquito vector Anopheles gambiae. Nature Biotechnology. 2016;34:78-83
  165. 165. Alphey L. Can CRISPR-Cas9 gene drives curb malaria? Nature Biotechnology. 2016;34(2):149-150
  166. 166. Reegan AD, Ceasar SA, Paulraj MG, Ignacimuthu S, Al-Dhabi NA. Current status of genome editing in vector mosquitoes: A review. Bioscience Trends. 2017;10(6):424-432
  167. 167. Waite JL, Lynch PA, Thomas MB. Eave tubes for malaria control in Africa: A modelling assessment of potential impact on transmission. Malaria Journal. 2016;15(1):449
  168. 168. Menger DJ, Omusula P, Holdinga M, Homan T, Carreira AS, Vandendaele P, et al. Field evaluation of a push-pull system to reduce malaria transmission. PLoS One. 2015;10(4):e0123415
  169. 169. Tusting LS, Thwing J, Sinclair D, Fillinger U, Gimnig J, Bonner KE, et al. Mosquito larval source management for controlling malaria. Cochrane Database of Systematic Reviews. 2013;8:Cd008923
  170. 170. Brady OJ, Godfray HC, Tatem AJ, Gething PW, Cohen JM, McKenzie FE, et al. Vectorial capacity and vector control: Reconsidering sensitivity to parameters for malaria elimination. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2016;110(2):107-117
  171. 171. Moreno M, Tong C, Guzman M, Chuquiyauri R, Llanos-Cuentas A, Rodriguez H, et al. Infection of laboratory-colonized Anopheles darlingi mosquitoes by Plasmodium vivax. The American Journal of Tropical Medicine and Hygiene. 2014;90(4):612-616
  172. 172. Villarreal-Trevino C, Vasquez GM, Lopez-Sifuentes VM, Escobedo-Vargas K, Huayanay-Repetto A, Linton YM, et al. Establishment of a free-mating, long-standing and highly productive laboratory colony of Anopheles darlingi from the Peruvian Amazon. Malaria Journal. 2015;14:227
  173. 173. Pinault LL, Hunter FF. Characterization of larval habitats of Anopheles albimanus, Anopheles pseudopunctipennis, Anopheles punctimacula, and Anopheles oswaldoi s.L. populations in lowland and highland Ecuador. Journal of Vector Ecology. 2012;37(1):124-136
  174. 174. Galardo AK, Zimmerman R, Galardo CD. Larval control of Anopheles (Nyssorhynchus) darlingi using granular formulation of Bacillus sphaericus in abandoned gold-miners excavation pools in the Brazilian Amazon rainforest. Revista da Sociedade Brasileira de Medicina Tropical. 2013;46(2):172-177

Written By

Jan Evelyn Conn, Maria Eugenia Grillet, Margarita Correa and Maria Anice Mureb Sallum

Submitted: 24 January 2018 Reviewed: 03 April 2018 Published: 18 July 2018