Open access peer-reviewed chapter

Ending Malaria Transmission in the Asia Pacific Malaria Elimination Network (APMEN) Countries: Challenges and the Way Forward

Written By

Kinley Wangdi and Archie CA Clements

Submitted: May 29th, 2017 Reviewed: February 13th, 2018 Published: July 18th, 2018

DOI: 10.5772/intechopen.75405

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Member countries in the Asia Pacific Malaria Elimination Network (APMEN) are pursuing the global goal of malaria elimination by 2030. Different countries are in various phases of malaria elimination and this review aims to present a compilation of available evidence on the challenges and way forward for malaria elimination in APMEN countries. Malaria transmission in these States is complex. APMEN member countries include the largest populations living in areas of malaria transmission risk outside Africa. They are a global source for spread of artemisinin-based combination therapy (ACT) resistance, include the biggest burden of Plasmodium vivax and zoonotic malaria, and face many geopolitical and socio-economic factors that will challenge malaria elimination efforts. These challenges can be addressed in part through operational research to identify country-specific solutions, making better use of operational data such as through spatial decision support system (SDSS) approaches, strengthening surveillance, and cross-border initiative for coordinated action.


  • Plasmodium falciparum
  • P. vivax
  • drug-resistance
  • malaria elimination
  • challenges

1. Background

Malaria imposes great health and socio-economic burden on humanity, with an estimated 3.2 billion people at risk of being infected with malaria [1]. In 2016, there were approximately 216 million cases with 445,000 deaths, most of which were in children aged under 5 years in Africa [2, 3]. However, substantial progress has been made in fighting malaria, with global incidence reducing by 41% and mortality rates by 62% between 2000 and 2015 [1]. In 2016, malaria remained endemic in 91 countries and territories as compared to 108 in 2000 [2]. It is estimated that most (90%) of total malaria cases were in the World Health Organisation (WHO) African Region, followed by the South-East Asian Region (SEAR) (7%) and the Eastern Mediterranean Region (2%) [4]. A number of factors have been attributed for this reduction, including wide-scale deployment of malaria control interventions, economic development in endemic countries, urbanisation, and unprecedented financial support for malaria control interventions [5, 6, 7, 8]. In 2016, an estimated US$ 2.7 billion was invested in malaria control and elimination efforts globally by governments of malaria endemic countries and international partners [1, 9].

Recognising the need to hasten progress in reducing the burden of malaria, WHO developed the Global Technical Strategy for Malaria 2016–2030(GTS) [5], which sets out a vision for accelerating progress towards malaria elimination. The WHO strategy is complemented by the Roll Back Malaria advocacy plan, Action and Investment to Defeat Malaria 2016–2030(AIM) [10]. GTS and AIM set an ambitious global target of eliminating malaria in at least 21 countries by 2020, identified as E-2020 countries by WHO and 35 countries by 2030 [1, 2, 10].

In line with the global efforts to eliminate malaria, the Asia Pacific Malaria Elimination Network (APMEN) was established in 2009, initially including 10 countries (Bhutan, China, Democratic People’s Republic of Korea (DPR Korea), Indonesia, Malaysia, the Philippines, Republic of Korea, Solomon Islands, Sri Lanka, and Vanuatu) that now have expanded to 18 countries (adding Bangladesh, Cambodia, Lao People’s Democratic Republic (Lao PDR), India, Nepal, Papua New Guinea, Thailand, and Vietnam) [11] (Figure 1). APMEN countries encompass the largest malaria reporting area outside the African region. APMEN serves the country partners and together with regional partners from the academic, development, non-governmental and private sectors, and global agencies including the WHO, collaboratively address the unique challenges of malaria elimination in the region through leadership, advocacy, capacity building, knowledge exchange and building evidence to support more effective, sustained malaria elimination programmes across the region [12].

Figure 1.

Member countries of the Asia Pacific Malaria Elimination Network countries (APMEN).

Each member State has defined elimination goals based on malaria transmission trends (Table 1). Countries with low incidence of malaria are targeting elimination at the national level, while countries with higher incidence are planning to eliminate malaria at the sub-national level before pursuing elimination at the national level. However, all countries are committed to eliminating malaria in the Asia Pacific region by 2030 [13]. Sri Lanka eliminated malaria in 2012 and WHO certified Sri Lanka malaria free nation in 2016 [14]. Bhutan and the Republic of Korea have targeted to eliminate malaria in 2018 and 2019 respectively [15, 16]. Bangladesh, China, Malaysia, Philippines, and Vanuatu plan to eliminate malaria by 2020; DPR Korea, Cambodia, Lao People’s Demographic Republic (Lao PDR), and Papua New Guinea (PNG) are planning to eliminate by 2025, and Nepal by 2026; finally India, Indonesia, Thailand, and Vietnam plan to eliminate malaria by 2030 [15]. The success of malaria elimination in APMEN States will greatly enhance the global drive towards malaria elimination. Therefore, the aim of this review is to present a compilation of available evidence on the challenges and way forward for malaria elimination in APMEN countries.

No. of cases/year
DPR Korea13,52016,76021,85014,41010,5408002700
Lao PDR51,00042,800112,70093,500117,30087,90027,390
Republic of Korea1300500400400600600600
Solomon Islands95,90066,20055,00056,40030,78039,40086,000
Sri Lanka

Table 1.

Malaria transmission trends in the Asia Pacific Malaria Elimination Network (APMEN) countries based on the estimated malaria cases during 2010–2016.

PNG, Papua New Guinea.

Source: World malaria report 2017 (WHO [1, 16])


2. Epidemiological drivers of malaria in APMEN countries

Malaria elimination in APMEN countries faces many challenges. The challenges include large numbers of people living in malaria risk areas; presence of all forms of human malaria: Plasmodium falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi; the high incidence of P. vivaxmalaria, which is particularly difficult to control due to the dormant stages of its life cycle within the human host, and zoonotic malaria caused by P. knowlesi, which has animal reservoirs; antimalarial drug resistance in P. falciparumand P. vivaxparasites; diverse vectors with different feeding behaviour and insecticide resistance; forest malaria; human migration across porous international borders and cross-border malaria; and inadequacies in health systems in the region.

2.1. Plasmodium vivaxMalaria

Plasmodium vivaxis an important but relatively neglected malaria parasite globally [17]. This form of malaria is more widespread than P. falciparummalaria with 2.9 billion people at risk of infection, of which 90% live in the Asia Pacific region [18, 19, 20, 21, 22]. P. vivaxis more difficult to treat than P. falciparumdue to dormant liver stages (hypnozoites) [23, 24, 25], and the development of transmissible blood stages (gametocytes) before clinical symptoms [26]. These characteristics enable the parasite to adapt to environmental challenges and evade control interventions in place and time.

In many countries embarking on malaria elimination, P. falciparumincidence declines more rapidly than P. vivaxincidence, due to the greater effectiveness of interventions for the former. Treating all stages of the parasite (radical cure) is a critical strategy for the successful control and ultimate elimination of P. vivax. In order to achieve radical cure of P. vivax, blood stage parasites, as well as the hypnozoites, need to be cleared. The only current widely available drug against hypnozoites is the 8-aminoquinoline compound, primaquine [27]. Unfortunately, individuals who have a genetic deficiency for glucose-6-phosphate dehydrogenase (G6PD) enzyme are at risk of severe haemolysis when treated with the drug [28, 29, 30]. In addition, primaquine requires prolonged daily administration over seven to 14 days. The complexities of prescribing reliable, safe and effective radical cure of P. vivaxhighlights the urgent need for innovative new approaches to assure schizonticidal and hypnozoiticidal treatment; without which, P. vivaxelimination is unlikely in most settings.

2.2. Zoonotic malaria

Plasmodium knowlesiinfections have been reported in a number of Asian Pacific countries [31, 32, 33, 34]. This zoonotic species of malaria, which also infects macaque monkeys that form the main animal reservoir, was probably present in humans but was undiagnosed until molecular detection methods were developed that could distinguish P. knowlesifrom the morphologically similar human malaria parasite Plasmodium malariae[35, 36]. Recently, the first case of human infection with Plasmodium cynomolgiwas reported in Peninsular Malaysia that resembles P. vivaxmorphologically [37]. The role of animal reservoirs of malaria transmittable to humans is an almost wholly neglected question in the elimination agenda in the Asia-Pacific region [38].

2.3. Characteristics of populations at risk

Nearly 2.1 billion people in the Asia-Pacific region live in areas where there is risk of malaria transmission of which 16.8% live in high-risk areas [2, 39] (Figure 2). These high-risk areas include settlements located in remote parts of endemic countries including border areas. Many of these high-risk areas are characterised by forest and forest fringe environment with high malaria transmission, poor geographical accessibility, high population mobility, and low human density. In addition, most of these areas are inhabited by ethnic minorities, refugees and displaced people who are difficult to access and often experience high degree of poverty [40, 41]. Furthermore, these areas are frequented by people engaged in activities with increased risk of malaria exposure, such as tourism and pilgrimages, forest-related work such as logging, gem-mining, latex harvesting, fishing, road construction and other industrial occupations [41, 42, 43, 44, 45].

Figure 2.

Population at risk of malaria in Asia Pacific Malaria Elimination Network (APMEN) countries for data based on 2016. (at risk- low risk + high risk). Source: World malaria report 2017 [1].

2.4. Antimalarial drug-resistance

Historically, countries in the Mekong Region including Cambodia and Thailand are global epicentres of emerging antimalarial drug resistance [46]. Chloroquine resistance was first reported in this area in the 1970s, followed by resistance to other anti-malarial drugs [47]. Over the past decade, artemisinin-based combination therapy (ACT) became the first-line protocol for the management of P. falciparuminfections world over. However, parasites that are drug-resistant to artemisinin and its derivatives have recently emerged in various parts of Southeast Asia challenging all control strategies for treatment and elimination efforts [48, 49, 50, 51]. Presently, resistance to mefloquine continues to be a concern in Thailand and Cambodia, where artesunate-mefloquine is used as first line treatment [47]. Artemether-lumefantrine remains highly effective in most parts of the world, with the exception of Cambodia [52, 53]. There are evidences of resistance to ACT in Vietnam [2, 54]. In India, ACT is used universally across the country yet declining efficacy to artesunate plus sulphadoxine-pyrimethamine has already been reported in its northeastern region [55, 56, 57] however, there have been no reports of ACT resistance in other APMEN member States (Figure 3).

Figure 3.

Distribution of malarial multidrug resistance for data based on 2016. ACT- artemisinin-based combination therapy; 1 ACT- resistance to one ACT; 2 ACT- resistance to two ACTs; 3 ACTs- resistance to three ACTs; 4 ACTs- resistance to four ACTs. Source: World malaria report 2017 [1].

Chloroquine has remained the main choice of treatment for P. vivaxblood stage infections, however, this policy is under threat from emerging drug resistant P. vivaxstrains [58]. A number of APMEN countries have reported P. vivaxresistance to chloroquine. There are reports of resistance in some States of India [59, 60, 61, 62], central Vietnam [63], and Thai-Myanmar border [64]. However, P. vivaxis still sensitive to chloroquine in Cambodia [65], border area of Yunnan Province of China and Myanmar [66], central China [67], and Nepal [68, 69].

2.5. Vector control

Vector control remains one of the main preventive strategies of containing malaria transmission in APMEN countries. However, a lack of technical capacity in entomology and vector control represents a key gap in elimination programmes. In addition, the diversity of malaria vectors in the Asia-Pacific region (19 different species) poses unique challenges for elimination [70, 71] (Table 2). There is considerable variation in bionomical characteristics of mosquito vectors making control efforts difficult. The commonest malaria vector species in the region, including Anopheles dirus, An. baimaii,and An. minimus[72, 73], are able to avoid indoor sprayed surfaces because of their exophilic and exophagic characteristics [70, 74, 75] rendering most domicile-based interventions, like long-lasting insecticidal nets (LLIN) and indoor residual spraying (IRS), less effective [74, 76]. Other challenges include insecticide resistance [77] and absence of local vector surveillance [78]. To address these challenges, APMEN instituted the APMEN Vector Control Working Group (VcWG) in 2010 [79]. The working group fosters information exchange between vector control experts and national programme managers of APMEN countries to formulate strategies to counter the challenges faced in the region. The Working Group has supported a range of activities to build vector control capacity in the region, including providing training fellowships to vector control officers in priority areas, supporting community efficacy studies of interventions, and consolidating information on vector management practices in the region [78].

Country°Main vectors*
Bangladesh [210]An. dirus, An. minimus, An. aconitus, An. philippinensis, An. sundaicus, An. barbirostris, An. subpictus, An. culicifacies, An. fluviatilis, An. maculatus
Bhutan [210]An. minimus
Cambodia [211]An. dirus, An. minimus, An. maculatus, An. epiroticus
China [73, 212]An. sinensis, An. lesteri, An. dirus, An. minimus, An. maculatus
DPR Korea [210]An. lesteri, An. sinensis, An. sineroides, An. kleini, An. yatsus hiroensis, An. lindesayi japonicas, An. koreicus
India [213]An. culicifacies, An. baimaii, An. fluviatilis, An. minimus, An. stephensi, An. maculatus, An. sundaicus
Indonesia [214]An. aconitus, An. balabacensis, An. bancrofti, An. barbirostris, An. barbumbrosus, An. farauti, An. flavirostris, An. karwari, An. kochi, An. koliensis, An. leucosphyrus, An. maculatus, An. nigerrimus, An. parangensis, An. punctulatus, An. sinensis, An. subpictus, An. sundaicus, An. tessellatus, An. vagus
Lao PDR [211]An. dirus, An. minimus, An. maculatus, An. jeyporiensis
Malaysia [211]An. balabacensis, An. campestris, An. cracens, An. donaldi, An. flavirostris, An. latens, An. letifer, An. maculatus, An. sundaicus
Nepal [210]An. fluviatilis, An. annularis, An. maculatus
Philippines [215]An. flavirostris, An. balabacensis, An. maculatus, An. litoralis, An. mangyanus
PNG [216, 217]An. farauti, An. koliensis, An. punctulatus, An. bancroftii, An. karwari
Republic of Korea [218]An. kleini, An. pullus, An. belenrae, An. sineroides, An. sinensis, An. lesteri
Solomon Islands [217]An. punctulatus, An. koliensis, An. farauti
Sri Lanka [210, 219]An. culicifacies, An. annularis, An. subpictus, An. tessellatus, An. stephensi
Thailand [210]An. dirus, An. minimus, An. maculatus, An. aconitus, An. epiroticus
Vanuatu [217]An. farauti
Vietnam [211]An. dirus, An. minimus, An. maculatus, An. aconitus, An. jeyporiensis, An. subpictus, An. sinensis, An. pampanai, An. epiroticus

Table 2.

List of the main malaria vectors in the Asia Pacific Malaria Elimination Network (APMEN) countries.

An., Anophelesnames refer either to the group, complex or species when specific identifications have been done.

Corresponding references are in brackets.

2.6. Forest malaria

Forest malaria constitutes bulk of transmission in APMEN countries [42, 43, 80, 81, 82, 83]. Many species of Anophelesmosquitoes that transmit malaria agents are abundant in natural forests and forested plantations. Both the forests and occurrence of deforestation impact increasing malaria risk and transmission, particularly in border areas. Forested areas provide conducive environment for vector proliferation and survival [84, 85]. Forest vectors usually prefer tree canopy coverage and are known to take shelter in tree holes [86, 87, 88]. Forest flora and sugar availability have also been shown to be crucial determinants of vectorial capacity [89]. In addition, leaves falling into larval habitats assure sustainable micro-climatic conditions for larvae of vectors like An. dirus,which is a dominant vector in Southeast Asia [90]. Further, there are usually abundant bodies of water including ponds, streams, and rivers in forested areas supporting vector multiplication and survival thereby sustaining malaria transmission in the region [80, 90, 91, 92, 93]. Deforestation increases the risk of malaria through a number of favourable conditions for the Anophelesmosquito by creating mosquito-breeding sites in the stumps of trees, ditches and puddles on the ground. The direct sunlight on the pools of water increases temperatures promoting mosquito breeding. Increased human activities in deforested areas such as logging, increased large-scale agricultural activities, mining, building of hydropower projects, and the collection of wood for fuel, all enhance contact with mosquitoes and thereby increased malaria transmission [94, 95, 96].

Populations in border areas are at greater risk of malaria infections because they frequently visit forests, forest fringe areas, or forested plantations at or near the border [42, 75, 97, 98]. Occupational exposures affect malarial receptivity by age group–for example, in forest fringe villages, adult infections are more prevalent due to forest-related activities such as logging, rubber tapping, bamboo cutting, charcoaling, foraging, and overnight stays in the forests [99]. Migration of the population working in the forest and forest fringe results in spread via carriers to new areas previously free from malaria transmission [100]. Despite high coverage of preventive measures such as LLIN or insecticide-treated nets (ITNs) and IRS in the member States of APMEN, populations working and staying overnight in the forest are not protected [43, 82, 101]. A lack of infrastructure such as roads and healthcare facilities hinder malaria control activities and delayed treatment.

2.7. Migration and cross-border malaria

One of the main challenges that continues thwart malaria elimination is cross-border malaria [94, 102]. People migrate across international borders for a number of reasons including work opportunities, visiting friends and relatives, and displacement as a result of natural and manmade calamities (such as ethnic conflicts) and major development projects. Malaria control in border areas is often difficult for being heavily forested, mountainous and inaccessible terrain, and unregulated population movements across the borders [103, 104]. Open porous international borders allow unchecked movement of people [105, 106, 107, 108, 109, 110, 111]. Such cross-border migration is likely to derail the malaria control activities of the neighbouring countries and risk introduction of drug-resistant parasites [112]. Mobile populations along the border areas often live in poverty and have poor access to healthcare services. Movement of people across international borders has contributed to maintaining high transmission hotspots adjacent to border points [73, 105, 113].

2.8. Misalignment of programmatic approaches

There are differences in programmatic approaches among neighbouring countries in the APMEN region making the coordination of control and preventive measures challenging [114, 115]. For example, there are differences in malaria control activities across Laos-Vietnam border. In Laos, the mainstay of malaria control is distribution of LLINs but on the Vietnamese side there is a stronger focus on IRS [114, 115]. Even where the approaches are similar, the specific antimalarial drugs or insecticides used can influence effectiveness due to parasite or vector resistance. Deltamethrin (synthetic pyrethroid) is used for IRS in Bhutan, however, DDT is used in the neighbouring State of Assam in India [116, 117, 118]. Effective control or elimination requires coordinated efforts for control interventions.


3. Way forward

In light of the aforementioned challenges in the APMEN member States, some of the possible solutions for way forward include carrying out operational research (OR) to understand the micro-epidemiology of malaria in each country, the use of technologically-assisted solutions for managing operational data (including spatial decision support systems (SDSS)), strengthening surveillance and initiating cross-border initiative.

3.1. Operational research (OR)

As countries move forward with malaria elimination, this effort requires adjustments on the way national malaria programmes operate. For example, the strategies for case detection and surveillance are radically different in control and elimination programmes. Countries may face constraints or bottlenecks as they make the transition from control to elimination for which OR can help to remove these bottlenecks, thereby enabling countries to make the transition from control to elimination phases more rapidly [119, 120]. OR in health is defined as search for knowledge on interventions, strategies, or tools that can enhance the quality, effectiveness, or coverage of programmes [121], and results in improved policy-making, better design and implementation of health systems, and more efficient methods of service delivery [122, 123, 124, 125]. The goal is to strengthen health services and improve healthcare delivery in disease-endemic countries and it has an additional critical role to play in helping solve major implementation problems [121, 126, 127, 128]. The key elements of OR are that the research questions are generated by identifying the constraints and challenges encountered during the implementation of programme activities, thus can be imbedded into routine programmatic activities [129]. The WHO and Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) have been encouraging programmes to conduct OR as part of their donor-funded activities [119, 130].

A significant limitation of national programmes has been the poor ability, even inability, to manage operational data collected through surveillance and other health information systems [131]. OR can be used to address these knowledge gaps and provide solutions to this limitation. OR has been under-utilised in APMEN member States [132, 133]. However, some countries including China [134], Bhutan [108], India [135, 136], Nepal [137], Solomon Islands [138], and countries in the Greater Mekong Sub-region (GMS) [120] are starting to address the challenges in malaria elimination efforts through OR in areas such as artemisinin resistance.

A key challenge is a lack of operational research capacity of member States [133]. One of the ways to overcome this shortcoming is to develop research capacity through the Structured Operational Research and Training Initiative (SORT IT), a global partnership-based initiative led by the Special Programme for Research and Training in Tropical Diseases (TDR) of WHO [131, 139, 140].

3.2. Role of geospatial data analysis

Malaria has a focal spatial distribution in pre-elimination and elimination phases, with hotspots of transmission in which the risk of malaria (including asymptomatic parasitaemias) and number of cases are higher than in surrounding areas [141, 142]. The scale at which spatial heterogeneity occurs ranges from micro-geographical setting beginning with household or village level [143, 144, 145, 146, 147, 148, 149] to municipalities [150], sub-districts [111], district [151, 152, 153], subnational [105, 154, 155, 156], national [40], regional [157], and global scales [70]. These spatial clusters of malaria have the potential to be sources of spread into neighbouring regions and countries if there is no focused intervention in the hotspot areas. Given the spatial heterogeneity of the disease, focused interventions in areas with higher incidence of disease are likely to have greater impact than uniform resource allocation [158]. Therefore, the spatial distribution of malaria and its interventions should be taken into account in national malaria elimination plans.

Risk mapping and temporal forecasting of malaria using environmental and climatic factors as spatial and/or temporal risk predictors has been routinely undertaken [107, 159, 160]. Environmental data for geospatial and temporal analysis can be collected through satellite sensors or meteorological stations [159, 160, 161, 162]. Image analysis techniques can be applied to satellite data to derive useful variables for the investigation of environmental drivers of malaria, such as land surface temperature, cold cloud duration (an indirect measure of rainfall), land use or land cover class, and normalised difference vegetation index (NDVI) [85, 161]. The NDVI can be used as proxy for rainfall through the measure of the greenness of the earth’s surface and hence vegetation cover [163]. Meteorological data can be interpolated with statistical techniques to estimate values of climatic variables, such as rainfall, temperature, and humidity, for locations where meteorological data are not available [164]. Currently these approaches have mainly been used in research context, and more research including OR needs to be conducted to establish how these approaches can be of practical benefit to malaria control and elimination programmes.

3.3. Spatial decision support systems

In recent years, spatial decision support systems (SDSSs) have been increasingly used in malaria elimination programmes in some countries of Asia-Pacific region to support planning, monitoring and evaluation, including Vanuatu, Solomon Islands and Bhutan [110, 165]. SDSSs have also been employed for other vector-borne disease control programmes such as dengue in Thailand and Singapore [166, 167, 168].

SDSSs are technology-driven systems for the collection, mapping, displaying and dissemination of disease data. They provide computerised support for decision making that helps spatially-explicit resource allocation decisions [107, 169]. Key elements of SDSS include: (i) data inputs from a variety of sources (including geospatial data layers), (ii) automated outputs to guide informed and strategic decision making for designated applications, (iii) enabling application/intervention outcomes re-entered back into the SDSS as a cyclical input, and (iv) expert knowledge integrated throughout all stages of the spatial decision support process [170] (Figure 4). In most recent examples, data are fed into the SDSS in the field using personal digital assistants (PDAs). The SDSS contains modules for planning, monitoring and evaluating coverage of target populations with IRS and LLINs, and for mapping malaria surveillance data. A mechanism is provided to link routinely collected data with associated spatial information. Spatial queries and analyses can be conducted and cartographic maps and reports of the areas of interest can be produced. Summary statistics of key indicators and maps are fed back to field teams to enhance implementation of interventions.

Figure 4.

Framework of spatial decision support system for malaria control and prevention with potential use in other vector borne diseases. (GIS geographical information system, PDA personnel digital assistant, GPS global positioning system, SDSS spatial decision support system, GR geographic reconnaissance, LLIN long-lasting insecticidal net, IRS indoor residual spraying, PCD passive case detection, RACD active case detection, JE Japanese encephalitis) (Wangdi et al. [110]).

Limited evaluation to date suggests that these systems support health programmes with a powerful and user-friendly operational tool for evidence-based decision making. Maps are an important SDSS output that provide a visual aid for decision making [170]. An example of map used to monitor LLIN coverage during a mass LLIN distribution in Bhutan is shown in Figure 5. This map can inform programme officials of the progress of the campaign and more importantly identifies areas that require catch up activities to achieve target coverage. Malaria incidence maps provide important inputs to policy makers to implement targeted interventions aimed at disease prevention and management. Spatial targeting of malaria interventions, supported by SDSS, will result in more efficient and effective allocation of intervention resources in transmission hotspots helping achieve substantial transmission reduction [135, 156, 158, 171].

Figure 5.

Sample output map for monitoring the coverage of long-lasting insecticidal net in Bhutan (Samdrup Jongkhar) (in this map there was no households without LLIN) (Wangdi et al. [110]).

3.4. Strengthening surveillance-response and cross-border initiatives

For countries embarking on malaria elimination, malaria surveillance systems need revamping. The main objectives of surveillance in malaria elimination are to detect infections (both symptomatic and asymptomatic), and ensure radical cure. This is in contrast to the malaria control phase in which the main objectives of surveillance is to quantify the level of malaria transmission and to support preventive action at the population level [172, 173]. In most countries, malaria surveillance is based on passive case detection. Passive surveillance involves reporting malaria cases by a health facility, which can be limited by incomplete reporting, healthcare seeking in the private sector (not captured by government systems), and poor diagnostic capacity, particularly in low transmission settings [174]. Prompt detection and radical treatment of imported malaria cases is critical for malaria elimination for sustaining the malaria elimination efforts. However, importation of malaria is inevitable, even in countries that have eliminated malaria. Passive case detection (PCD) could capture imported cases and allow interventions that would prevent resurgence in the presence of robust health system [175]. However, in areas with high transmission intensities in APMEN countries [70, 176], and unchecked migration across borders [103, 104, 105, 106, 107, 108, 109, 110, 111], there is likely to be significant transmission even in low transmission settings. Therefore, imported infections must be prevented through border screening, regional and cross-border initiatives and dialogue, proactive case detection, and treatment in high-risk population groups and travellers preventing resurgence of the disease [177].

Active surveillance addresses some of the limitations of PCD and generally involves cross-sectional surveys of defined sample populations, where the primary malaria indicator is the proportion of persons infected with malaria parasites (parasite prevalence) [178]. These surveys enable detection of asymptomatic infections that perpetuate transmission [179], and provide an opportunity to concurrently assess coverage of malaria interventions [180], but they are expensive and difficult to implement, and are not efficient in low-transmission settings.

One of the most efficient ways to enhance passive surveillance is through reactive case detection (RACD). When an index case of clinical malaria is detected in a community, RACD is carried out in all the households located within a certain distance of the index case. During the RACD, follow-up activities differ widely and can include testing of fever using RDTs or microscopy for any residual malaria infection and treating those who test positive. In addition, vector control activities including IRS and LLINs are intensified. RACD has been implemented in Africa and Asia with mixed results [110, 181, 182, 183, 184, 185, 186]. Nevertheless, RACD provides an opportunity for public health workers to concurrently assess coverage of malaria interventions including LLINs, and should be advocated and practised. Another efficient way to evaluate the efficacy of vector control methods, also applied in Africa and Asia, is to estimate the human antibody response to Anophelessaliva in human populations [187, 188, 189].

Diagnostic techniques used for testing blood during RACD will significantly impact the programme effectiveness. Estimating parasite prevalence using microscopy is time and labour intensive, and often inaccurate in operational settings [190]. Newly available rapid diagnostic tests (RDTs) offer on-the-spot results, but have limitations in specificity, sensitivity, quality, and cost [190, 191, 192, 193]. Both methods (microscopy and RDTs) may fail to detect a substantial proportion of low-density parasitaemias [186, 194, 195]. Polymerase chain reaction (PCR) provides enhanced sensitivity but results are not available immediately [196], instead Real-time PCR may present a consistent, accurate, and efficient tool for surveillance to assist malaria elimination in the future [196].

Cross-border movement of populations impacts the maintenance of ‘hotspots’ of high transmission along international borders [77, 94, 97, 108, 137, 197, 198, 199, 200], and spread of drug-resistance seen along the international border of Thailand and Cambodia [201]. Then, cross-border initiatives should be initiated through sharing of programme data including insecticide resistance, blood testing at the border areas, and treatment of symptomatic cases [177, 202, 203, 204, 205, 206, 207, 208]. Such successful cross-border case studies in the region have led to significant reduction in malaria burden in the study areas [209].


4. Conclusions

Successful malaria elimination in the APMEN member States will greatly enhance the global drive to eliminate malaria. Malaria transmission in these States is complex. APMEN member States include the largest populations living in areas of malaria transmission risk outside Africa. They are a global source of ACT resistance, highest burden of P. vivaxand zoonotic malaria, and face many geopolitical and socioeconomic factors that will challenge malaria elimination efforts. These challenges can be addressed in part through operational research to identify country specific solutions, making better use of operational data such as through implementing SDSS approaches, and strengthening surveillance and cross-border collaborations.



ACTartemisinin-based combination therapy
AIMaction and investment to defeat malaria 2016–2030
APMENAsia Pacific Malaria Elimination Network
DPR KoreaDemocratic People’s Republic of Korea
G6PDglucose-6-phosphate dehydrogenase
GFATMGlobal Fund to Fight AIDS, Tuberculosis and Malaria
GISgeographic information systems
GMSGreater Mekong Sub-region
GSTGlobal Technical Strategy for Malaria
IRSindoor residual spraying
ITNinsecticide-treated nets
Lao PDRLao People’s Demographic Republic
LLINlong-lasting insecticidal nets
MISmalaria indicator survey
NDVInormalised difference vegetation index
ORoperational research
PCDpassive case detection
PCRpolymerase chain reaction
RACDreactive case detection
RDTrapid diagnostic test
PNGPapua New Guinea
SDSSspatial decision support systems
SEARSouth-East Asian Region
SORT ITStructured Operational Research and Training Initiative
TDRResearch and Training in Tropical Diseases
VcWGVector Control Working Group
WHOWorld Health Organisation


  1. 1. WHO. World Malaria Report 2017. Geneva, Switzerland: WHO Library Cataloguing-in-Publication Data; 2017
  2. 2. WHO. World Malaria Report 2016. Switzerland: WHO Library Cataloguing-in-Publication Data Geneva; 2016
  3. 3. Malaria; 2016. []
  4. 4. WHO. World Malaria Report 2014. Switzerland: World Health Organization, Geneva, Switzerland, Geneva; 2014
  5. 5. WHO. Global Technical Strategy for Malaria 2016-2030. WHO Library Cataloguing-in-Publication Data; 2015
  6. 6. Wang SQ, Li YC, Zhang ZM, Wang GZ, Hu XM, Qualls WA, Xue RD. Prevention measures and socio-economic development result in a decrease in malaria in Hainan, China. Malaria Journal. 2014;13:362
  7. 7. Tusting LS, Willey B, Lucas H, Thompson J, Kafy HT, Smith R, Lindsay SW. Socioeconomic development as an intervention against malaria: A systematic review and meta-analysis. Lancet. 2013;382:963-972
  8. 8. Datta SC, Reimer JJ. Malaria and economic development. Review of Development Economics. 2013;17:1-15
  9. 9. Malaria; 2017. []
  10. 10. Action and Investiment to Defeat Malaria 2016-2030; 2015. []
  11. 11. Gosling RD, Whittaker M, Gueye CS, Fullman N, Baquilod M, Kusriastuti R, Feachem RG. Malaria elimination gaining ground in the Asia Pacific. Malaria Journal. 2012;11:346
  12. 12. APMEN: Elimination 2030: Working Together for a Malria-free Aisa Pacific. 2014;2017.[]
  13. 13. Chairman's Statement of 9th East Asia Summit; 2014. []
  14. 14. WHO certifies Sri Lanka malaria-free; 2016. []
  15. 15. Malaria elimination goals; 2015. []
  16. 16. WHO: Malaria Control and Elimination in the Western Pacific (2016-2020). (Pacific WHOROftW ed. Manila, Philippines. 2017
  17. 17. Feachem RG, Phillips AA, Hwang J, Cotter C, Wielgosz B, Greenwood BM, Sabot O, Rodriguez MH, Abeyasinghe RR, Ghebreyesus TA, Snow RW. Shrinking the malaria map: Progress and prospects. Lancet. 2010;376:1566-1578
  18. 18. Baird JK. Neglect ofPlasmodium vivaxmalaria. Trends in Parasitology. 2007;23:533-539
  19. 19. Ballut PC, Siqueira AM, Orlando AC, Alexandre MA, Alecrim MG, Lacerda MV. Prevalence and risk factors associated to pruritus inPlasmodium vivaxpatients using chloroquine in the Brazilian Amazon. Acta Tropica. 2013;128:504-508
  20. 20. Mendis K, Sina BJ, Marchesini P, Carter R. The neglected burden ofPlasmodium vivaxmalaria. The American Journal of Tropical Medicine and Hygiene. 2001;64:97-106
  21. 21. Sharma VP, Dev V, Phookan S. NeglectedPlasmodium vivaxmalaria in northeastern states of India. The Indian Journal of Medical Research. 2015;141:546-555
  22. 22. Waheed AA, Ghanchi NK, Rehman KA, Raza A, Mahmood SF, Beg MA. Vivax malaria and chloroquine resistance: A neglected disease as an emerging threat. Malaria Journal. 2015;14:146
  23. 23. Gray KA, Dowd S, Bain L, Bobogare A, Wini L, Shanks GD, Cheng Q. Population genetics ofPlasmodium falciparumandPlasmodium vivaxand asymptomatic malaria in Temotu Province, Solomon Islands. Malaria Journal. 2013;12:429
  24. 24. Noviyanti R, Coutrier F, Utami RA, Trimarsanto H, Tirta YK, Trianty L, Kusuma A, Sutanto I, Kosasih A, Kusriastuti R, et al. Contrasting transmission dynamics of co-endemicPlasmodium vivaxandP. falciparum: Implications for malaria control and elimination. PLoS Neglected Tropical Diseases. 2015;9:e0003739
  25. 25. Jennison C, Arnott A, Tessier N, Tavul L, Koepfli C, Felger I, Siba PM, Reeder JC, Bahlo M, Mueller I, Barry AE.Plasmodium vivaxpopulations are more genetically diverse and less structured than sympatricPlasmodium falciparumpopulations. PLoS Neglected Tropical Diseases. 2015;9:e0003634
  26. 26. Bousema T, Drakeley C. Epidemiology and infectivity ofPlasmodium falciparumandPlasmodium vivaxgametocytes in relation to malaria control and elimination. Clinical Microbiology Reviews. 2011;24:377-410
  27. 27. Domingo GJ, Satyagraha AW, Anvikar A, Baird K, Bancone G, Bansil P, Carter N, Cheng Q, Culpepper J, Eziefula C, et al. G6PD testing in support of treatment and elimination of malaria: Recommendations for evaluation of G6PD tests. Malaria Journal. 2013;12:391
  28. 28. von Seidlein L, Auburn S, Espino F, Shanks D, Cheng Q, McCarthy J, Baird K, Moyes C, Howes R, Menard D, et al. Review of key knowledge gaps in glucose-6-phosphate dehydrogenase deficiency detection with regard to the safe clinical deployment of 8-aminoquinoline treatment regimens: A workshop report. Malaria Journal. 2013;12:112
  29. 29. Cappellini MD, Fiorelli G. Glucose-6-phosphate dehydrogenase deficiency. Lancet. 2008;371:64-74
  30. 30. Howes RE, Battle KE, Satyagraha AW, Baird JK, Hay SI. G6PD deficiency: Global distribution, genetic variants and primaquine therapy. Advances in Parasitology. 2013;81:133-201
  31. 31. Moyes CL, Henry AJ, Golding N, Huang Z, Singh B, Baird JK, Newton PN, Huffman M, Duda KA, Drakeley CJ, et al. Defining the geographical range of thePlasmodium knowlesireservoir. PLoS Neglected Tropical Diseases. 2014;8:e2780
  32. 32. Khim N, Siv S, Kim S, Mueller T, Fleischmann E, Singh B, Divis PC, Steenkeste N, Duval L, Bouchier C, et al.Plasmodium knowlesiinfection in humans, Cambodia, 2007-2010. Emerging Infectious Diseases. 2011;17:1900-1902
  33. 33. Ta TT, Salas A, Ali-Tammam M, Martinez Mdel C, Lanza M, Arroyo E, Rubio JM. First case of detection ofPlasmodium knowlesiin Spain by real time PCR in a traveller from Southeast Asia. Malaria Journal. 2010;9:219
  34. 34. Lubis IND, Wijaya H, Lubis M, Lubis CP, Divis PCS, Beshir KB, Sutherland CJ. Contribution ofPlasmodium knowlesito multispecies human malaria infections in north Sumatera, Indonesia. The Journal of Infectious Diseases. 2017;215:1148-1155
  35. 35. Singh B, Kim Sung L, Matusop A, Radhakrishnan A, Shamsul SS, Cox-Singh J, Thomas A, Conway DJ. A large focus of naturally acquiredPlasmodium knowlesiinfections in human beings. Lancet. 2004;363:1017-1024
  36. 36. Singh B, Daneshvar C. Human infections and detection ofPlasmodium knowlesi. Clinical Microbiology Reviews. 2013;26:165-184
  37. 37. Ta TH, Hisam S, Lanza M, Jiram AI, Ismail N, Rubio JM. First case of a naturally acquired human infection withPlasmodium cynomolgi. Malaria Journal. 2014;13:68
  38. 38. Baird JK. Asia-Pacific malaria is singular, pervasive, diverse and invisible. International Journal for Parasitology. 2017;47:371-377
  39. 39. Overview: Malaria in the Asia-Pacific; 2014. []
  40. 40. Bui HM, Clements AC, Nguyen QT, Nguyen MH, Le XH, Hay SI, Tran TH, Wertheim HF, Snow RW, Horby P. Social and environmental determinants of malaria in space and time in Viet Nam. International Journal for Parasitology. 2011;41:109-116
  41. 41. Erhart A, Ngo DT, Phan VK, Ta TT, Van Overmeir C, Speybroeck N, Obsomer V, Le XH, Le KT, Coosemans M, D'Alessandro U. Epidemiology of forest malaria in Central Vietnam: A large scale cross-sectional survey. Malaria Journal. 2005;4:58
  42. 42. Erhart A, Thang ND, Hung NQ, Toi le V, Hung le X, Tuy TQ, Cong le D, Speybroeck N, Coosemans M, D'Alessandro U. Forest malaria in Vietnam: A challenge for control. American Journal of Tropical Medicine and Hygiene. 2004;70:110-118
  43. 43. Grietens KP, Xuan XN, Ribera J, Duc TN, Bortel W, Ba NT, Van KP, Xuan HL, D'Alessandro U, Erhart A. Social determinants of long lasting insecticidal hammock use among the Ra-glai ethnic minority in Vietnam: Implications for forest malaria control. PLoS One. 2012;7:e29991
  44. 44. Liu Y, Hsiang MS, Zhou H, Wang W, Cao Y, Gosling RD, Cao J, Gao Q. Malaria in overseas labourers returning to China: An analysis of imported malaria in Jiangsu Province, 2001-2011. Malaria Journal. 2014;13:29
  45. 45. Pichainarong N, Chaveepojnkamjorn W. Malaria infection and life-style factors among hilltribes along the Thai-Myanmar border area, northern Thailand. The Southeast Asian Journal of Tropical Medicine and Public Health. 2004;35:834-839
  46. 46. WHO: Containment of Malaria Multi-Drug Resistance on the Cambodia-Thailand Border. WHO-Mekong Malaria Programme; 2007
  47. 47. Satimai W, Sudathip P, Vijaykadga S, Khamsiriwatchara A, Sawang S, Potithavoranan T, Sangvichean A, Delacollette C, Singhasivanon P, Kaewkungwal J, Lawpoolsri S. Artemisinin resistance containment project in Thailand. II: Responses to mefloquine-artesunate combination therapy among falciparum malaria patients in provinces bordering Cambodia. Malaria Journal. 2012;11:300
  48. 48. Dondorp AM, Fairhurst RM, Slutsker L, Macarthur JR, Breman JG, Guerin PJ, Wellems TE, Ringwald P, Newman RD, Plowe CV. The threat of artemisinin-resistant malaria. The New England Journal of Medicine. 2011;365:1073-1075
  49. 49. Enserink M. Malaria's drug miracle in danger. Science. 2010;328:844-846
  50. 50. Dondorp AM, Nosten F, Yi P, Das D, Phyo AP, Tarning J, Lwin KM, Ariey F, Hanpithakpong W, Lee SJ, et al. Artemisinin resistance inPlasmodium falciparummalaria. The New England Journal of Medicine. 2009;361:455-467
  51. 51. Ashley EA, Dhorda M, Fairhurst RM, Amaratunga C, Lim P, Suon S, Sreng S, Anderson JM, Mao S, Sam B, et al. Spread of artemisinin resistance inPlasmodium falciparummalaria. The New England Journal of Medicine. 2014;371:411-423
  52. 52. WHO. Global report on antimalarial drug efficacy and drug resistance: 2000-2010. WHO Library Cataloguing-in-Publication Data; 2010
  53. 53. Noedl H, Se Y, Schaecher K, Smith BL, Socheat D, Fukuda MM. Evidence of artemisinin-resistant malaria in western Cambodia. The New England Journal of Medicine. 2008;359:2619-2620
  54. 54. Hien TT, Thuy-Nhien NT, Phu NH, Boni MF, Thanh NV, Nha-Ca NT, Thai le H, Thai CQ, Toi PV, Thuan PD, et al. In vivo susceptibility ofPlasmodium falciparumto artesunate in Binh Phuoc Province, Vietnam. Malaria Journal. 2012;11:355
  55. 55. Mishra N, Prajapati SK, Kaitholia K, Bharti RS, Srivastava B, Phookan S, Anvikar AR, Dev V, Sonal GS, Dhariwal AC, et al. Surveillance for artemisinin resistance inPlasmodium falciparumin India using the kelch13 molecular marker. Antimicrobial Agents and Chemotherapy. 2015;59:2548-2553
  56. 56. Saha P, Guha SK, Das S, Mullick S, Ganguly S, Biswas A, Bera DK, Chattopadhyay G, Das M, Kundu PK, et al. Comparative efficacies of artemisinin combination therapies inPlasmodium falciparummalaria and polymorphism of pfATPase6, pfcrt, pfdhfr, and pfdhps genes in tea gardens of Jalpaiguri District, India. Antimicrobial Agents and Chemotherapy. 2012;56:2511-2517
  57. 57. Patel P, Bharti PK, Bansal D, Ali NA, Raman RK, Mohapatra PK, Sehgal R, Mahanta J, Sultan AA, Singh N. Prevalence of mutations linked to antimalarial resistance inPlasmodium falciparumfrom Chhattisgarh, Central India: A malaria elimination point of view. Scientific Reports. 2017;7:16690
  58. 58. Price RN, von Seidlein L, Valecha N, Nosten F, Baird JK, White NJ. Global extent of chloroquine-resistantPlasmodium vivax: A systematic review and meta-analysis. The Lancet Infectious Diseases. 2014;14:982-991
  59. 59. Srivastava HC, Yadav RS, Joshi H, Valecha N, Mallick PK, Prajapati SK, Dash AP. Therapeutic responses ofPlasmodium vivaxandP. falciparumto chloroquine, in an area of western India whereP. vivaxpredominates. Annals of Tropical Medicine and Parasitology. 2008;102:471-480
  60. 60. Adak T, Sharma VP, Orlov VS. Studies on thePlasmodium vivaxrelapse pattern in Delhi, India. The American Journal of Tropical Medicine and Hygiene. 1998;59:175-179
  61. 61. Yadav RS, Ghosh SK. Radical curative efficacy of five-day regimen of primaquine for treatment ofPlasmodium vivaxmalaria in India. The Journal of Parasitology. 2002;88:1042-1044
  62. 62. Singh RK. Emergence of chloroquine-resistant vivax malaria in South Bihar (India). Transactions of the Royal Society of Tropical Medicine and Hygiene. 2000;94:327
  63. 63. Thanh PV, Hong NV, Van NV, Louisa M, Baird K, Xa NX, Peeters Grietens K, Hung le X, Duong TT, Rosanas-Urgell A, et al. ConfirmedPlasmodium vivaxresistance to chloroquine in Central Vietnam. Antimicrobial Agents and Chemotherapy. 2015;59:7411-7419
  64. 64. Rungsihirunrat K, Muhamad P, Chaijaroenkul W, Kuesap J, Na-Bangchang K.Plasmodium vivaxdrug resistance genes; Pvmdr1 and Pvcrt-o polymorphisms in relation to chloroquine sensitivity from a malaria endemic area of Thailand. The Korean Journal of Parasitology. 2015;53:43-49
  65. 65. Amaratunga C, Sreng S, Mao S, Tullo GS, Anderson JM, Chuor CM, Suon S, Fairhurst RM. Chloroquine remains effective for treatingPlasmodium vivaxmalaria in Pursat province, Western Cambodia. Antimicrobial Agents and Chemotherapy. 2014;58:6270-6272
  66. 66. Liu H, Yang HL, Tang LH, Li XL, Huang F, Wang JZ, Li CF, Wang HY, Nie RH, Guo XR, et al. MonitoringPlasmodium vivaxchloroquine sensitivity along China-Myanmar border of Yunnan Province, China during 2008-2013. Malaria Journal. 2014;13:364
  67. 67. Lu F, Wang B, Cao J, Sattabongkot J, Zhou H, Zhu G, Kim K, Gao Q, Han ET. Prevalence of drug resistance-associated gene mutations inPlasmodium vivaxin Central China. The Korean Journal of Parasitology. 2012;50:379-384
  68. 68. Ranjitkar S, Schousboe ML, Thomsen TT, Adhikari M, Kapel CM, Bygbjerg IC, Alifrangis M. Prevalence of molecular markers of anti-malarial drug resistance inPlasmodium vivaxandPlasmodium falciparumin two districts of Nepal. Malaria Journal. 2011;10:75
  69. 69. Pant DK, Joshi AB, Lekhak B. Assessment of therapeutic efficacy of anti malarial drug (Chloroquine) againstPlasmodium vivaxmalaria in Kanchanpur District. Journal of Nepal Health Research Council. 2006;4:41-45
  70. 70. Sinka ME, Bangs MJ, Manguin S, Rubio-Palis Y, Chareonviriyaphap T, Coetzee M, Mbogo CM, Hemingway J, Patil AP, Temperley WH, et al. A global map of dominant malaria vectors. Parasites & Vectors. 2012;5:69
  71. 71. Morgan K, Somboon P, Walton C. UnderstandingAnophelesdiversity in Southeast Asia and its applications for malaria control. In: Manguin S, editor.AnophelesMosquitoes - New Insights into Malaria Vectors. Rijeka: InTech; 2013. Ch. 11
  72. 72. Dev V, Manguin S. Biology, distribution and control ofAnopheles (Cellia) minimusin the context of malaria transmission in northeastern India. Parasites & Vectors. 2016;9:585
  73. 73. Zhang S, Guo S, Feng X, Afelt A, Frutos R, Zhou S, Manguin S.Anophelesvectors in mainland China while approaching malaria elimination. Trends in Parasitology. 2017;33:889-900
  74. 74. Trung HD, Bortel WV, Sochantha T, Keokenchanh K, Briet OJ, Coosemans M. Behavioural heterogeneity ofAnophelesspecies in ecologically different localities in Southeast Asia: A challenge for vector control. Tropical Medicine & International Health. 2005;10:251-262
  75. 75. Manh CD, Beebe NW, Van VN, Quang TL, Lein CT, Nguyen DV, Xuan TN, Ngoc AL, Cooper RD. Vectors and malaria transmission in deforested, rural communities in north-Central Vietnam. Malaria Journal. 2010;9:259
  76. 76. Somboon P, Lines J, Aramrattana A, Chitprarop U, Prajakwong S, Khamboonruang C. Entomological evaluation of community-wide use of lambdacyhalothrin-impregnated bed nets against malaria in a border area of north-West Thailand. Transactions of the Royal Society of Tropical Medicine and Hygiene. 1995;89:248-254
  77. 77. Dhiman S, Goswami D, Rabha B, Gopalakrishnan R, Baruah I, Singh L. Malaria epidemiology along indo-Bangladesh border in Tripura state, India. The Southeast Asian Journal of Tropical Medicine and Public Health. 2010;41:1279-1289
  78. 78. Vector control; 2010. []
  79. 79. APMEN: APMEN Vector Working Group (VcWG): Vector Control Working Group Objectives and Governance. APMEN; 2010. []
  80. 80. Bharti PK, Chand SK, Singh MP, Mishra S, Shukla MM, Singh R, Singh N. Emergence of a new focus ofPlasmodium malariaein forest villages of district Balaghat, Central India: Implications for the diagnosis of malaria and its control. Tropical Medicine & International Health. 2013;18:12-17
  81. 81. Sharma SK, Tyagi PK, Padhan K, Upadhyay AK, Haque MA, Nanda N, Joshi H, Biswas S, Adak T, Das BS, et al. Epidemiology of malaria transmission in forest and plain ecotype villages in Sundargarh District, Orissa, India. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2006;100:917-925
  82. 82. Van Bortel W, Trung HD, Hoi le X, Van Ham N, Van Chut N, Luu ND, Roelants P, Denis L, Speybroeck N, D'Alessandro U, Coosemans M. Malaria transmission and vector behaviour in a forested malaria focus in Central Vietnam and the implications for vector control. Malaria Journal. 2010;9:373
  83. 83. Durnez L, Mao S, Denis L, Roelants P, Sochantha T, Coosemans M. Outdoor malaria transmission in forested villages of Cambodia. Malaria Journal. 2013;12:329
  84. 84. O'Loughlin SM, Okabayashi T, Honda M, Kitazoe Y, Kishino H, Somboon P, Sochantha T, Nambanya S, Saikia PK, Dev V, Walton C. Complex population history of twoAnopheles dirusmosquito species in Southeast Asia suggests the influence of Pleistocene climate change rather than human-mediated effects. Journal of Evolutionary Biology. 2008;21:1555-1569
  85. 85. Haque U, Hashizume M, Glass GE, Dewan AM, Overgaard HJ, Yamamoto T. The role of climate variability in the spread of malaria in Bangladeshi highlands. PLoS One. 2010;5:e14341
  86. 86. Zhou G, Munga S, Minakawa N, Githeko AK, Yan G. Spatial relationship between adult malaria vector abundance and environmental factors in western Kenya highlands. The American Journal of Tropical Medicine and Hygiene. 2007;77:29-35
  87. 87. Yadav RS, Sharma VP, Chand SK. Mosquito breeding and resting in treeholes in a forest ecosystem in Orissa. Indian Journal of Malariology. 1997;34:8-16
  88. 88. Gunasekaran K, Sahu SS, Parida SK, Sadanandane C, Jambulingam P, Das PK. Anopheline fauna of Koraput district, Orissa state, with particular reference to transmission of malaria. The Indian Journal of Medical Research. 1989;89:340-343
  89. 89. Manda H, Gouagna LC, Foster WA, Jackson RR, Beier JC, Githure JI, Hassanali A. Effect of discriminative plant-sugar feeding on the survival and fecundity ofAnopheles gambiae. Malaria Journal. 2007;6:113
  90. 90. Obsomer V, Defourny P, Coosemans M. TheAnopheles diruscomplex: Spatial distribution and environmental drivers. Malaria Journal. 2007;6:26
  91. 91. Sahu SS, Parida SK, Sadanandane C, Gunasekaran K, Jambulingam P, Das PK. Breeding habitats of malaria vectors:A. fluviatilis,A. annularisandA. culicifacies, in Koraput district, Orissa. Indian Journal of Malariology. 1990;27:209-216
  92. 92. Kumar DS, Andimuthu R, Rajan R, Venkatesan MS. Spatial trend, environmental and socioeconomic factors associated with malaria prevalence in Chennai. Malaria Journal. 2014;13:14
  93. 93. Sharma VP, Dev V. Biology & control ofAnopheles culicifaciesGiles 1901. The Indian Journal of Medical Research. 2015;141:525-536
  94. 94. Wangdi K, Gatton ML, Kelly GC, Clements AC. Cross-border malaria: A major obstacle for malaria elimination. Advances in Parasitology. 2015;89:79-107
  95. 95. Hahn MB, Gangnon RE, Barcellos C, Asner GP, Patz JA. Influence of deforestation, logging, and fire on malaria in the Brazilian Amazon. PLoS One. 2014;9:e85725
  96. 96. Guerra CA, Snow RW, Hay SI. A global assessment of closed forests, deforestation and malaria risk. Annals of Tropical Medicine and Parasitology. 2006;100:189-204
  97. 97. Chaveepojnkamjorn W, Pichainarong N. Malaria infection among the migrant population along the Thai-Myanmar border area. The Southeast Asian Journal of Tropical Medicine and Public Health. 2004;35:48-52
  98. 98. Tangena JA, Thammavong P, Wilson AL, Brey PT, Lindsay SW. Risk and control of mosquito-borne diseases in southeast Asian rubber plantations. Trends in Parasitology. 2016;32:402-415
  99. 99. Dysoley L, Kaneko A, Eto H, Mita T, Socheat D, Borkman A, Kobayakawa T. Changing patterns of forest malaria among the mobile adult male population in Chumkiri District, Cambodia. Acta Tropica. 2008;106:207-212
  100. 100. Wisit Chaveepojnkamjorn D. Behavioral factors and malaria infection among the migrant population, Chiang Rai province. Journal of the Medical Association of Thailand. 2005;88:1293-1301
  101. 101. Singh N, Singh OP, Sharma VP. Dynamics of malaria transmission in forested and deforested regions of Mandla District, Central India (Madhya Pradesh). Journal of the American Mosquito Control Association. 1996;12:225-234
  102. 102. Hlongwana KW, Tsoka-Gwegweni J. Towards the implementation of malaria elimination policy in South Africa: The stakeholders' perspectives. Global Health Action. 2017;10:1288954
  103. 103. Stern A. International population movements and public health in the Mekong region: An overview of some issues concerning mapping. The Southeast Asian Journal of Tropical Medicine and Public Health. 1998;29:201-212
  104. 104. Xu J, Liu H. The challenges of malaria elimination in Yunnan Province, People's Republic of China. The Southeast Asian Journal of Tropical Medicine and Public Health. 2012;43:819-824
  105. 105. Clements A, Barnett AG, Cheng ZW, Snow RW, Zhou HN. Space-time variation of malaria incidence in Yunnan province, China. Malaria Journal. 2009;8:18
  106. 106. Hu H, Singhasivanon P, Salazar NP, Thimasarn K, Li X, Wu Y, Yang H, Zhu D, Supavej S, Looarecsuwan S. Factors influencing malaria endemicity in Yunnan Province, PR China (analysis of spatial pattern by GIS). Geographical information system. The Southeast Asian Journal of Tropical Medicine and Public Health. 1998;29:191-200
  107. 107. Reid H, Haque U, Clements AC, Tatem AJ, Vallely A, Ahmed SM, Islam A, Haque R. Mapping malaria risk in Bangladesh using Bayesian geostatistical models. The American Journal of Tropical Medicine and Hygiene. 2010;83:861-867
  108. 108. Wangdi K, Banwell C, Gatton ML, Kelly GC, Namgay R, Clements AC. Malaria burden and costs of intensified control in Bhutan, 2006-14: An observational study and situation analysis. The Lancet Global Health. 2016;4:e336-e343
  109. 109. Mohapatra PK, Narain K, Prakash A, Bhattacharyya DR, Mahanta J. Risk factors of malaria in the fringes of an evergreen monsoon forest of Arunachal Pradesh. National Medical Journal of India. 2001;14:139-142
  110. 110. Wangdi K, Banwell C, Gatton ML, Kelly GC, Namgay R, Clements AC. Development and evaluation of a spatial decision support system for malaria elimination in Bhutan. Malaria Journal. 2016;15:180
  111. 111. Wangdi K, Kaewkungwal J, Singhasivanon P, Silawan T, Lawpoolsri S, White NJ. Spatio-temporal patterns of malaria infection in Bhutan: A country embarking on malaria elimination. Malaria Journal. 2011;10:89
  112. 112. Childs DZ, Cattadori IM, Suwonkerd W, Prajakwong S, Boots M. Spatiotemporal patterns of malaria incidence in northern Thailand. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2006;100:623-631
  113. 113. Carme B. Substantial increase of malaria in inland areas of eastern French Guiana. Tropical Medicine & International Health. 2005;10:154-159
  114. 114. Anh NQ, Hung le X, Thuy HN, Tuy TQ, Caruana SR, Biggs BA, Morrow M. KAP surveys and malaria control in Vietnam: Findings and cautions about community research. The Southeast Asian Journal of Tropical Medicine and Public Health 2005;36:572-577
  115. 115. Hung le Q, Vries PJ, Giao PT, Nam NV, Binh TQ, Chong MT, Quoc NT, Thanh TN, Hung LN, Kager PA. Control of malaria: A successful experience from Viet Nam. Bulletin of the World Health Organization. 2002;80:660-666
  116. 116. Dev V, Phookan S, Sharma VP, Dash AP, Anand SP. Malaria parasite burden and treatment seeking behavior in ethnic communities of Assam, northeastern India. The Journal of Infection. 2006;52:131-139
  117. 117. Mittal PK, Wijeyaratne P, Pandey S. Status of insecticide resistance of malaria, Kala-azar and Japanese encephalitis vectors in Bangladesh, Bhutan, India and Nepal (BBIN). Environmental Health Project Activity Report. 2004;129:44-48
  118. 118. Wangdi K, Singhasivanon P, Silawan T, Lawpoolsri S, White NJ, Kaewkungwal J. Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan. Malaria Journal. 2010;9:251
  119. 119. WHO. Planning Meeting for Operational Research on Malaria Elimination. Geneva, Switzerland; 2014
  120. 120. Guyant P, Corbel V, Guerin PJ, Lautissier A, Nosten F, Boyer S, Coosemans M, Dondorp AM, Sinou V, Yeung S, White N. Past and new challenges for malaria control and elimination: The role of operational research for innovation in designing interventions. Malaria Journal. 2015;14:279
  121. 121. Zachariah R, Harries AD, Ishikawa N, Rieder HL, Bissell K, Laserson K, Massaquoi M, Van Herp M, Reid T. Operational research in low-income countries: What, why, and how? The Lancet Infectious Diseases. 2009;9:711-717
  122. 122. Nunn P, Harries A, Godfrey-Faussett P, Gupta R, Maher D, Raviglione M. The research agenda for improving health policy, systems performance, and service delivery for tuberculosis control: A WHO perspective. Bulletin of the World Health Organization. 2002;80:471-476
  123. 123. Reynolds J. Introduction. Socio-Economic Planning Sciences. 1987;21:73-77
  124. 124. Datta S. Applications of O.R. in health in developing countries: A review. Social Science & Medicine. 1993;37:1441-1450
  125. 125. Harries AD. Integration of operational research into National Tuberculosis Control Programmes. Tuberculosis (Edinburgh, Scotland). 2003;83:143-147
  126. 126. Operational and Implementation research; 2016. []
  127. 127. Malhotra S, Zodpey SP. Operations research in public health. Indian Journal of Public Health. 2010;54:145-150
  128. 128. Monks T. Operational research as implementation science: Definitions, challenges and research priorities. Implementation Sci. 2016;11:1-10
  129. 129. Mahendradhata Y, Probandari A, Widjanarko B, Riono P, Mustikawati D, Tiemersma EW, Alisjahbana B. Embedding operational research into national disease control programme: Lessons from 10 years of experience in Indonesia. Global Health Action. 2014;7:25412
  130. 130. WHO. Guide to Operational Research in programs supported by the global fund; 2016. []
  131. 131. Zachariah R, Ford N, Maher D, Bissell K, Van den Bergh R, van den Boogaard W, Reid T, Castro KG, Draguez B, von Schreeb J, et al. Is operational research delivering the goods? The journey to success in low-income countries. The Lancet Infectious Diseases. 2012;12:415-421
  132. 132. Zhou SS, Rietveld AE, Velarde-Rodriguez M, Ramsay AR, Zhang SS, Zhou XN, Cibulskis RE. Operational research on malaria control and elimination: A review of projects published between 2008 and 2013. Malaria Journal. 2014;13:473
  133. 133. Ramsay A, Olliaro P, Reeder JC. The need for operational research and capacity-building in support of the global technical strategy for malaria 2016-2030. Malaria Journal. 2016;15:235
  134. 134. Chen SB, Ju C, Chen JH, Zheng B, Huang F, Xiao N, Zhou X, Ernest T, Zhou XN. Operational research needs toward malaria elimination in China. Advances in Parasitology. 2014;86:109-133
  135. 135. Srivastava A, Nagpal B, Joshi P, Paliwal J, Dash A. Identification of malaria hot spots for focused intervention in tribal state of India: A GIS based approach. International Journal of Health Geographics. 2009;8:30
  136. 136. Dev V, Sangma BM, Dash AP. Persistent transmission of malaria in Garo hills of Meghalaya bordering Bangladesh, north-East India. Malaria Journal. 2010;9:263
  137. 137. Dhimal M, O'Hara RB, Karki R, Thakur GD, Kuch U, Ahrens B. Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal. Malaria Journal. 2014;13:457
  138. 138. Atkinson JA, Johnson ML, Wijesinghe R, Bobogare A, Losi L, O'Sullivan M, Yamaguchi Y, Kenilorea G, Vallely A, Cheng Q, et al. Operational research to inform a sub-national surveillance intervention for malaria elimination in Solomon Islands. Malaria Journal. 2012;11:101
  139. 139. Ramsay A, Harries AD, Zachariah R, Bissell K, Hinderaker SG, Edginton M, Enarson DA, Satyanarayana S, Kumar AM, Hoa NB, et al. The structured operational research and training initiative for public health programmes. Public Health Action. 2014;4:79-84
  140. 140. Zachariah R, Rust S, Berger SD, Guillerm N, Bissell K, Delaunois P, Reid AJ, Kumar AM, Olliaro PL, Reeder JC, et al. Building global capacity for conducting operational research using the SORT IT model: Where and who? PLoS One. 2016;11:e0160837
  141. 141. Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, Ghani A, Drakeley C, Gosling R. Hitting hotspots: Spatial targeting of malaria for control and elimination. PLoS Medicine. 2012;9:e1001165
  142. 142. Ernst KC, Adoka SO, Kowuor DO, Wilson ML, John CC. Malaria hotspot areas in a highland Kenya site are consistent in epidemic and non-epidemic years and are associated with ecological factors. Malaria Journal. 2006;5:78
  143. 143. Alemu K, Worku A, Berhane Y, Kumie A. Spatiotemporal clusters of malaria cases at village level, Northwest Ethiopia. Malaria Journal. 2014;13:223
  144. 144. Rosas-Aguirre A, Ponce OJ, Carrasco-Escobar G, Speybroeck N, Contreras-Mancilla J, Gamboa D, Pozo E, Herrera S, Llanos-Cuentas A.Plasmodium vivaxmalaria at households: Spatial clustering and risk factors in a low endemicity urban area of the northwestern Peruvian coast. Malaria Journal. 2015;14:176
  145. 145. Pinchoff J, Henostroza G, Carter BS, Roberts ST, Hatwiinda S, Hamainza B, Hawela M, Curriero FC. Spatial patterns of incident malaria cases and their household contacts in a single clinic catchment area of Chongwe District, Zambia. Malaria Journal. 2015;14:305
  146. 146. Ayele DG, Zewotir TT, Mwambi HG. Spatial distribution of malaria problem in three regions of Ethiopia. Malaria Journal. 2013;12:207
  147. 147. Rosas-Aguirre A, Speybroeck N, Llanos-Cuentas A, Rosanas-Urgell A, Carrasco-Escobar G, Rodriguez H, Gamboa D, Contreras-Mancilla J, Alava F, Soares IS, et al. Hotspots of malaria transmission in the Peruvian Amazon: Rapid assessment through a parasitological and serological survey. PLoS One. 2015;10:e0137458
  148. 148. Rulisa S, Kateera F, Bizimana JP, Agaba S, Dukuzumuremyi J, Baas L, de Dieu Harelimana J, Mens PF, Boer KR, de Vries PJ. Malaria prevalence, spatial clustering and risk factors in a low endemic area of eastern Rwanda: A cross sectional study. PLoS One. 2013;8:e69443
  149. 149. Wen L, Li C, Lin M, Yuan Z, Huo D, Li S, Wang Y, Chu C, Jia R, Song H. Spatio-temporal analysis of malaria incidence at the village level in a malaria-endemic area in Hainan, China. Malaria Journal. 2011;10:88
  150. 150. Braz RM, Guimaraes RF, Carvalho Junior OA, Tauil PL. Spatial dependence of malaria epidemics in municipalities of the Amazonian ecosystem. Revista Brasileira de Epidemiologia. 2014;17:615-628
  151. 151. Brooker S, Clarke S, Njagi JK, Polack S, Mugo B, Estambale B, Muchiri E, Magnussen P, Cox J. Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya. Tropical Medicine & International Health. 2004;9:757-766
  152. 152. Haque U, Huda M, Hossain A, Ahmed SM, Moniruzzaman M, Haque R. Spatial malaria epidemiology in Bangladeshi highlands. Malaria Journal. 2009;8:185
  153. 153. Ahmed S, Galagan S, Scobie H, Khyang J, Prue CS, Khan WA, Ram M, Alam MS, Haq MZ, Akter J, et al. Malaria hotspots drive hypoendemic transmission in the Chittagong Hill districts of Bangladesh. PLoS One. 2013;8:e69713
  154. 154. Kohara Melchior LA, Chiaravalloti Neto F. Spatial and spatio-temporal analysis of malaria in the state of acre, western Amazon, Brazil. Geospatial Health. 2016;11:443
  155. 155. Sluydts V, Heng S, Coosemans M, Van Roey K, Gryseels C, Canier L, Kim S, Khim N, Siv S, Mean V, et al. Spatial clustering and risk factors of malaria infections in Ratanakiri Province, Cambodia. Malaria Journal. 2014;13:387
  156. 156. Zhang W, Wang L, Fang L, Ma J, Xu Y, Jiang J, Hui F, Wang J, Liang S, Yang H, Cao W. Spatial analysis of malaria in Anhui province, China. Malaria Journal. 2008;7:206
  157. 157. Gething PW, Casey DC, Weiss DJ, Bisanzio D, Bhatt S, Cameron E, Battle KE, Dalrymple U, Rozier J, Rao PC, et al. MappingPlasmodium falciparummortality in Africa between 1990 and 2015. The New England Journal of Medicine. 2016;375:2435-2445
  158. 158. Clements ACA, Reid HL, Kelly GC, Hay SI. Further shrinking the malaria map: How can geospatial science help to achieve malaria elimination? The Lancet Infectious Diseases. 2013;13:709-718
  159. 159. Hay SI, Tatem AJ, Graham AJ, Goetz SJ, Rogers DJ. Global environmental data for mapping infectious disease distribution. Advances in Parasitology. 2006;62:37-77
  160. 160. Yang GJ, Gao Q, Zhou SS, Malone JB, McCarroll JC, Tanner M, Vounatsou P, Bergquist R, Utzinger J, Zhou XN. Mapping and predicting malaria transmission in the People's Republic of China, using integrated biology-driven and statistical models. Geospatial Health. 2010;5:11-22
  161. 161. Dlamini SN, Franke J, Vounatsou P. Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data. Geospatial Health. 2015;10:302
  162. 162. Kamanga A, Renn S, Pollard D, Bridges DJ, Chirwa B, Pinchoff J, Larsen DA, Winters AM. Open-source satellite enumeration to map households: Planning and targeting indoor residual spraying for malaria. Malaria Journal. 2015;14:345
  163. 163. Sudre B, Rossi M, Van Bortel W, Danis K, Baka A, Vakalis N, Semenza JC. Mapping environmental suitability for malaria transmission, Greece. Emerging Infectious Diseases. 2013;19:784-786
  164. 164. Hay SI, Lennon JJ. Deriving meteorological variables across Africa for the study and control of vector-borne disease: A comparison of remote sensing and spatial interpolation of climate. Tropical Medicine & International Health. 1999;4:58-71
  165. 165. Kelly GC, Seng CM, Donald W, Taleo G, Nausien J, Batarii W, Iata H, Tanner M, Vestergaard LS, Clements AC. A spatial decision support system for guiding focal indoor residual interventions in a malaria elimination zone. Geospatial Health. 2011;6:21-31
  166. 166. Sithiprasasna R, Patpoparn S, Attatippaholkun W, Suvannadabba S, Srisuphanunt M. The geographic information system as an epidemiological tool in the surveillance of dengue virus-infectedAedesmosquitos. The Southeast Asian Journal of Tropical Medicine and Public Health. 2004;35:918-926
  167. 167. Teng TB. New initiatives in dengue control in Singapore. Dengue Bulletin. 2001;25:1-6
  168. 168. Ai-Leen GT, Song RJ. The use of GIS in ovitrap monitoring for dengue control in Singapore. Dengue Bulletin. 2000;24:110-116
  169. 169. Keenan PB. Spatial Decision Support Systems: Decision Making Support Systems: Achievements and Challenges for the New Decade. Idea Group Publishing; 2003
  170. 170. Kelly GC, Tanner M, Vallely A, Clements A. Malaria elimination: Moving forward with spatial decision support systems. Trends in Parasitology. 2012;28:297-304
  171. 171. Mendis K. Spatial technology & malaria control. The Indian Journal of Medical Research. 2009;130:498-500
  172. 172. WHO. Disease Surveillance for Malaria Elimination: An Operational Manual. World Health Organization. Switzerland: Geneva; 2012
  173. 173. WHO. Disease Surveillance for Malaria Control. Geneva, Switzerland: World Health Organization; 2012
  174. 174. Singh N, Bharti PK, Kumre NS. Active v. Passive surveillance for malaria in remote tribal belt of Central India: Implications for malaria elimination. Pathogens and Global Health. 2016;110:178-184
  175. 175. Moonen B, Cohen JM, Snow RW, Slutsker L, Drakeley C, Smith DL, Abeyasinghe RR, Rodriguez MH, Maharaj R, Tanner M, Targett G. Operational strategies to achieve and maintain malaria elimination. Lancet. 2010;376:1592-1603
  176. 176. Walton C, Handley JM, Tun-Lin W, Collins FH, Harbach RE, Baimai V, Butlin RK. Population structure and population history ofAnopheles dirusmosquitoes in Southeast Asia. Molecular Biology and Evolution. 2000;17:962-974
  177. 177. Sturrock HJ, Roberts KW, Wegbreit J, Ohrt C, Gosling RD. Tackling imported malaria: An elimination endgame. The American Journal of Tropical Medicine and Hygiene. 2015;93:139-144
  178. 178. Hay SI, Smith DL, Snow RW. Measuring malaria endemicity from intense to interrupted transmission. The Lancet Infectious Diseases. 2008;8:369-378
  179. 179. Alves FP, Gil LH, Marrelli MT, Ribolla PE, Camargo EP, Da Silva LH. Asymptomatic carriers ofPlasmodiumspp. as infection source for malaria vector mosquitoes in the Brazilian Amazon. Journal of Medical Entomology. 2005;42:777-779
  180. 180. WHO. Malaria indicator survey: basic documentation for survey design and implementation/Roll Back Malaria Monitoring and Evaluation Reference Group. 1211 Geneva 27, Switzerland; 2005
  181. 181. Cotter C, Sudathip P, Herdiana H, Cao Y, Liu Y, Luo A, Ranasinghe N, Bennett A, Cao J, Gosling RD. Piloting a programme tool to evaluate malaria case investigation and reactive case detection activities: Results from 3 settings in the Asia Pacific. Malaria Journal. 2017;16:347
  182. 182. Hustedt J, Canavati SE, Rang C, Ashton RA, Khim N, Berne L, Kim S, Sovannaroth S, Ly P, Menard D, et al. Reactive case-detection of malaria in Pailin Province, western Cambodia: Lessons from a year-long evaluation in a pre-elimination setting. Malaria Journal. 2016;15:132
  183. 183. Larsen DA, Chisha Z, Winters B, Mwanza M, Kamuliwo M, Mbwili C, Hawela M, Hamainza B, Chirwa J, Craig AS, et al. Malaria surveillance in low-transmission areas of Zambia using reactive case detection. Malaria Journal. 2015;14:465
  184. 184. Parker DM, Landier J, von Seidlein L, Dondorp A, White L, Hanboonkunupakarn B, Maude RJ, Nosten FH. Limitations of malaria reactive case detection in an area of low and unstable transmission on the Myanmar-Thailand border. Malaria Journal. 2016;15:571
  185. 185. Rossi G, Van den Bergh R, Nguon C, Debackere M, Vernaeve L, Khim N, Kim S, Menard D, De Smet M, Kindermans JM. Adapting reactive case detection strategies for falciparum malaria in a low-transmission area in Cambodia. Clinical Infectious Diseases. 2017
  186. 186. Sturrock HJ, Novotny JM, Kunene S, Dlamini S, Zulu Z, Cohen JM, Hsiang MS, Greenhouse B, Gosling RD. Reactive case detection for malaria elimination: Real-life experience from an ongoing program in Swaziland. PLoS One. 2013;8:e63830
  187. 187. Brosseau L, Drame PM, Besnard P, Toto JC, Foumane V, Le Mire J, Mouchet F, Remoue F, Allan R, Fortes F, et al. Human antibody response toAnophelessaliva for comparing the efficacy of three malaria vector control methods in Balombo, Angola. PLoS One. 2012;7:e44189
  188. 188. Drame PM, Poinsignon A, Marie A, Noukpo H, Doucoure S, Cornelie S, Remoue F. New salivary biomarkers of human exposure to malaria vector bites. In: Manguin S, editor.AnophelesMosquitoes - New Insights into Malaria Vectors. Rijeka: InTech; 2013 Ch. 23
  189. 189. Ya-Umphan P, Cerqueira D, Parker DM, Cottrell G, Poinsignon A, Remoue F, Brengues C, Chareonviriyaphap T, Nosten F, Corbel V. Use of anAnophelessalivary biomarker to assess malaria transmission risk along the Thailand-Myanmar border. The Journal of Infectious Diseases. 2017;215:396-404
  190. 190. Wongsrichanalai C, Barcus MJ, Muth S, Sutamihardja A, Wernsdorfer WH. A review of malaria diagnostic tools: Microscopy and rapid diagnostic test (RDT). The American Journal of Tropical Medicine and Hygiene. 2007;77:119-127
  191. 191. Chiodini PL, Bowers K, Jorgensen P, Barnwell JW, Grady KK, Luchavez J, Moody AH, Cenizal A, Bell D. The heat stability ofPlasmodiumlactate dehydrogenase-based and histidine-rich protein 2-based malaria rapid diagnostic tests. Transactions of the Royal Society of Tropical Medicine and Hygiene. 2007;101:331-337
  192. 192. Maltha J, Gillet P, Jacobs J. Malaria rapid diagnostic tests in endemic settings. Clinical Microbiology and Infection. 2013;19:399-407
  193. 193. Murray CK, Gasser RA Jr, Magill AJ, Miller RS. Update on rapid diagnostic testing for malaria. Clinical Microbiology Reviews. 2008;21:97-110
  194. 194. Littrell M, Sow GD, Ngom A, Ba M, Mboup BM, Dieye Y, Mutombo B, Earle D, Steketee RW. Case investigation and reactive case detection for malaria elimination in northern Senegal. Malaria Journal. 2013;12:331
  195. 195. Lin JT, Saunders DL, Meshnick SR. The role of submicroscopic parasitemia in malaria transmission: What is the evidence? Trends in Parasitology. 2014;30:183-190
  196. 196. Rogawski ET, Congpuong K, Sudathip P, Satimai W, Sug-aram R, Aruncharus S, Darakapong A, Kitchakarn S, Meshnick SR. Active case detection with pooled real-time PCR to eliminate malaria in Trat province, Thailand. The American Journal of Tropical Medicine and Hygiene. 2012;86:789-791
  197. 197. Delacollette C, D'Souza C, Christophel E, Thimasarn K, Abdur R, Bell D, Dai TC, Gopinath D, Lu S, Mendoza R, et al. Malaria trends and challenges in the Greater Mekong subregion. The Southeast Asian Journal of Tropical Medicine and Public Health. 2009;40:674-691
  198. 198. Haque U, Overgaard HJ, Clements AC, Norris DE, Islam N, Karim J, Roy S, Haque W, Kabir M, Smith DL, Glass GE. Malaria burden and control in Bangladesh and prospects for elimination: An epidemiological and economic assessment. The Lancet Global Health. 2014;2:e98-105
  199. 199. Dev V, Sharma VP, Hojai D. Malaria transmission and disease burden in Assam: Challenges and opportunities. Journal of Parasitic Diseases. 2009;33:13-22
  200. 200. Jitthai N. Migration and malaria. The Southeast Asian Journal of Tropical Medicine and Public Health. 2013;44(Suppl 1):166-200 discussion 306-167
  201. 201. Bhumiratana A, Intarapuk A, Sorosjinda-Nunthawarasilp P, Maneekan P, Koyadun S. Border malaria associated with multidrug resistance on Thailand-Myanmar and Thailand-Cambodia borders: Transmission dynamic, vulnerability, and surveillance. BioMed Research International. 2013;2013:363417
  202. 202. Edwards HM, Canavati SE, Rang C, Ly P, Sovannaroth S, Canier L, Khim N, Menard D, Ashton RA, Meek SR, Roca-Feltrer A. Novel cross-border approaches to optimise identification of asymptomatic and Artemisinin-resistantPlasmodiuminfection in mobile populations crossing Cambodian Borders. PLoS One. 2015;10:e0124300
  203. 203. Yangzom T, Gueye CS, Namgay R, Galappaththy GN, Thimasarn K, Gosling R, Murugasampillay S, Dev V. Malaria control in Bhutan: Case study of a country embarking on elimination. Malaria Journal. 2012;11:9
  204. 204. Blumberg L, Frean J, Moonasar D. Successfully controlling malaria in South Africa. South African Medical Journal. 2014;104:224-227
  205. 205. Gueye CS, Teng A, Kinyua K, Wafula F, Gosling R, McCoy D. Parasites and vectors carry no passport: How to fund cross-border and regional efforts to achieve malaria elimination. Malaria Journal. 2012;11:344
  206. 206. Wen S, Harvard KE, Gueye CS, Canavati SE, Chancellor A, Ahmed BN, Leaburi J, Lek D, Namgay R, Surya A, et al. Targeting populations at higher risk for malaria: A survey of national malaria elimination programmes in the Asia Pacific. Malaria Journal. 2016;15:271
  207. 207. Wondji CS, Coleman M, Kleinschmidt I, Mzilahowa T, Irving H, Ndula M, Rehman A, Morgan J, Barnes KG, Hemingway J. Impact of pyrethroid resistance on operational malaria control in Malawi. Proceedings of the National Academy of Sciences of the United States of America. 2012;109:19063-19070
  208. 208. Sonkong K, Chaiklieng S, Neave P, Suggaravetsiri P. Factors affecting delay in seeking treatment among malaria patients along Thailand-Myanmar border in Tak Province, Thailand. Malaria Journal. 2015;14:3
  209. 209. Xu JW, Li Y, Yang HL, Zhang J, Zhang ZX, Yang YM, Zhou HN, Havumaki J, Li HX, Liu H, et al. Malaria control along China-Myanmar border during 2007-2013: An integrated impact evaluation. Infectious Diseases of Poverty. 2016;5:75
  210. 210. SEARO: Malaria vectors of South-East Asia. SEARO W ed. 2017
  211. 211. Suwonkerd W, Ritthison W, Ngo CT, Tainchum K, Bangs MJ, Chareonviriyaphap T. Vector biology and malaria transmission in Southeast Asia. In: Manguin S, editor.AnophelesMosquitoes - New Insights into Malaria Vectors. Rijeka: InTech; 2013 Ch. 10
  212. 212. Huang JX, Xia ZG, Zhou SS, Pu XJ, Hu MG, Huang DC, Ren ZP, Zhang SS, Yang MN, Wang DQ, Wang JF. Spatio-temporal analysis of malaria vectors in national malaria surveillance sites in China. Parasites & Vectors. 2015;8:146
  213. 213. Wangdi K, Gatton ML, Kelly GC, Banwell C, Dev V, Clements AC. Malaria elimination in India and regional implications. The Lancet Infectious Diseases. 2016;16:e214-e224
  214. 214. Elyazar IR, Sinka ME, Gething PW, Tarmidzi SN, Surya A, Kusriastuti R, Winarno BJK, Hay SI, Bangs MJ. The distribution and bionomics ofAnophelesmalaria vector mosquitoes in Indonesia. Advances in Parasitology. 2013;83:173-266
  215. 215. WHO. Case Study on Malaria Elimination in the Philippines Launched. Geneva 27, Switzerland: WHO; 2015
  216. 216. Cooper RD, Waterson DG, Frances SP, Beebe NW, Pluess B, Sweeney AW. Malaria vectors of Papua New Guinea. International Journal for Parasitology. 2009;39:1495-1501
  217. 217. Beebe NW, Russell TL, Burkot TR, Lobo NF, Cooper RD. The systematics and bionomics of malaria vectors in the Southwest Pacific. In: Manguin S, editor.AnophelesMosquitoes - New Insights into Malaria Vectors. Rijeka: InTech; 2013. Ch. 12
  218. 218. Chang KS, Yoo DH, Ju YR, Lee WG, Roh JY, Kim HC, Klein TA, Shin EH. Distribution of malaria vectors and incidence of vivax malaria at Korean army installations near the demilitarized zone, Republic of Korea. Malaria Journal. 2016;15:259
  219. 219. Gayan Dharmasiri AG, Perera AY, Harishchandra J, Herath H, Aravindan K, Jayasooriya HTR, Ranawaka GR, Hewavitharane M. First record ofAnopheles stephensiin Sri Lanka: A potential challenge for prevention of malaria reintroduction. Malaria Journal. 2017;16:326

Written By

Kinley Wangdi and Archie CA Clements

Submitted: May 29th, 2017 Reviewed: February 13th, 2018 Published: July 18th, 2018