Characteristics of HIV positive women in Vulindlela and Greater Edendale, KwaZulu-Natal, South Africa, 2014–2015.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"2816",leadTitle:null,fullTitle:"Toxoplasmosis - Recent Advances",title:"Toxoplasmosis",subtitle:"Recent Advances",reviewType:"peer-reviewed",abstract:'A ubiquitous organism able to infect all mammals and birds, which has been estimated to infect one third of the global human population, Toxoplasma gondii is the most successful parasite on Earth, and toxoplasmosis a major zoonotic disease. A current approach to this zoonosis is the "one health" concept, based on the understanding that a disease occurring between animals and man in a specific environment can only be dealt with at the interface of all "players" involved. 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The magnitude of the effect of interventions that modify one Quality Adjusted Life Years (QALYs) will be compared, and the transferability of these interventions globally will be investigated by comparison between different socio-economic countries with different government structures (from socialist to autocratic). The reproducibility and cost of the lifestyle interventions (e.g., exercise, sleep, nutritious diet, national child care, pollution limitations) on QALYs will also be documented. The ratio of (QALY/Cost) weighted by reproducibility and transferability should give a rank-ordered list of actions humans can take to increase the quality years of human consciousness. Differences in the optimized list of rank-ordered interventions to maximize the quality of life between nation-states with varying GDP and government types (i.e., the lack of transferability) will be discussed. 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Fernando Díez-Higuera",slug:"j.-fernando-diez-higuera"}]},{id:"15376",title:"Using Emergence Phenomenon in Meaningful Image Segmentation for Content-based Image Retrieval",slug:"using-emergence-phenomenon-in-meaningful-image-segmentation-for-content-based-image-retrieval",signatures:"Sagarmay Deb",authors:[{id:"22115",title:"Dr.",name:"Sagarmay",middleName:null,surname:"Deb",fullName:"Sagarmay Deb",slug:"sagarmay-deb"}]},{id:"15377",title:"Dual Active Contour Models for Medical Image Segmentation",slug:"dual-active-contour-models-for-medical-image-segmentation",signatures:"Gilson Giraldi, Paulo Rodrigues, Jasjit Suri and Sameer Singh",authors:[{id:"19215",title:"Dr.",name:"Gilson",middleName:null,surname:"Giraldi",fullName:"Gilson Giraldi",slug:"gilson-giraldi"},{id:"19566",title:"Dr.",name:"Paulo",middleName:null,surname:"Rodrigues",fullName:"Paulo Rodrigues",slug:"paulo-rodrigues"},{id:"22481",title:"Dr.",name:"Jasjit",middleName:null,surname:"Suri",fullName:"Jasjit Suri",slug:"jasjit-suri"},{id:"22482",title:"Dr.",name:"Sameer",middleName:null,surname:"Singh",fullName:"Sameer Singh",slug:"sameer-singh"}]},{id:"15378",title:"Image Segmentation Using Maximum Spanning Tree on Affinity Matrix",slug:"image-segmentation-using-maximum-spanning-tree-on-affinity-matrix",signatures:"Qiang He and Chee-Hung Henry Chu",authors:[{id:"10743",title:"Dr.",name:"Qiang",middleName:null,surname:"He",fullName:"Qiang He",slug:"qiang-he"},{id:"22082",title:"Dr.",name:"Henry",middleName:null,surname:"Chu",fullName:"Henry Chu",slug:"henry-chu"}]},{id:"15379",title:"Image Segmentation by Autoregressive Time Series Model",slug:"image-segmentation-by-autoregressive-time-series-model",signatures:"Pei-Gee Peter Ho",authors:[{id:"21284",title:"Dr.",name:"Pei-Gee",middleName:null,surname:"Ho",fullName:"Pei-Gee Ho",slug:"pei-gee-ho"}]},{id:"15380",title:"Evolutionary-based Image Segmentation Methods",slug:"evolutionary-based-image-segmentation-methods",signatures:"Licheng Jiao",authors:[{id:"14343",title:"Prof.",name:"Fang",middleName:null,surname:"Liu",fullName:"Fang Liu",slug:"fang-liu"},{id:"14348",title:"Prof.",name:"Licheng",middleName:null,surname:"Jiao",fullName:"Licheng Jiao",slug:"licheng-jiao"},{id:"21379",title:"Prof.",name:"Shuang",middleName:null,surname:"Wang",fullName:"Shuang Wang",slug:"shuang-wang"},{id:"23216",title:"Prof",name:"Maoguo",middleName:null,surname:"Gong",fullName:"Maoguo Gong",slug:"maoguo-gong"},{id:"23217",title:"Dr.",name:"Jingjing",middleName:null,surname:"Ma",fullName:"Jingjing Ma",slug:"jingjing-ma"}]},{id:"15381",title:"Segmentation of Handwritten Document Images into Text Lines",slug:"segmentation-of-handwritten-document-images-into-text-lines",signatures:"Vassilis Katsouros and Vassilis Papavassiliou",authors:[{id:"22496",title:"Dr.",name:"Vassilis",middleName:null,surname:"Katsouros",fullName:"Vassilis Katsouros",slug:"vassilis-katsouros"},{id:"22498",title:"Dr.",name:"Vassilis",middleName:null,surname:"Papavassiliou",fullName:"Vassilis Papavassiliou",slug:"vassilis-papavassiliou"}]},{id:"15382",title:"IR Image Segmentation by Combining Genetic Algorithm and Multi-scale Edge Detection",slug:"ir-image-segmentation-by-combining-genetic-algorithm-and-multi-scale-edge-detection",signatures:"Li Zhaohui and Chen Ming",authors:[{id:"18520",title:"Dr.",name:"Zhaohui",middleName:null,surname:"Li",fullName:"Zhaohui Li",slug:"zhaohui-li"}]},{id:"15383",title:"Segmentation of Remotely Sensed Imagery: Moving from Sharp Objects to Fuzzy Regions",slug:"segmentation-of-remotely-sensed-imagery-moving-from-sharp-objects-to-fuzzy-regions",signatures:"Ivan Lizarazo and Paul Elsner",authors:[{id:"19431",title:"Mr.",name:"Paul",middleName:null,surname:"Elsner",fullName:"Paul Elsner",slug:"paul-elsner"},{id:"20771",title:"Dr.",name:"Ivan",middleName:null,surname:"Lizarazo",fullName:"Ivan Lizarazo",slug:"ivan-lizarazo"}]},{id:"15388",title:"Color-based Texture Image Segmentation for Vehicle Detection",slug:"color-based-texture-image-segmentation-for-vehicle-detection",signatures:"Ricardo Mejía-Iñigo, María E. 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A. A. Raof, M. Y. Mashor, R. B. Ahmad and S. S. M. Noor",authors:[{id:"12388",title:"Dr.",name:"R. Badlishah",middleName:null,surname:"Ahmad",fullName:"R. Badlishah Ahmad",slug:"r.-badlishah-ahmad"},{id:"22111",title:"Prof.",name:"Mohd. Yusoff",middleName:null,surname:"Mashor",fullName:"Mohd. Yusoff Mashor",slug:"mohd.-yusoff-mashor"},{id:"22112",title:"Dr.",name:"Rafikha Aliana",middleName:null,surname:"A Raof",fullName:"Rafikha Aliana A Raof",slug:"rafikha-aliana-a-raof"},{id:"22632",title:"Prof.",name:"Siti Suraiya",middleName:null,surname:"Md. Noor",fullName:"Siti Suraiya Md. 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by",editors:[{id:"17084",title:"Dr.",name:"Hanna",surname:"Goszczynska",slug:"hanna-goszczynska",fullName:"Hanna Goszczynska"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"82367",title:"Spatial Variation and Factors Associated with Unsuppressed HIV Viral Load among Women in an HIV Hyperendemic Area of KwaZulu-Natal, South Africa",doi:"10.5772/intechopen.105547",slug:"spatial-variation-and-factors-associated-with-unsuppressed-hiv-viral-load-among-women-in-an-hiv-hype",body:'In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS) set ambitious 90–90-90 HIV testing and treatment target to achieve the 73% composite viral suppression target by the year 2020 towards ending the epidemic by year 2030 [1]. While few countries like Australia and Botswana achieved this target [2, 3], the global public health community failed to achieve this target [4]. Therefore, in 2021 the UNAIDS Global AIDS strategy raised the targets to 95–95-95 with an overall viral suppression of 86% to be met by 2025 including prioritising sexual reproductive health and rights for women living with HIV (WLHIV), with the aim of controlling the epidemic by the year 2030 [5]. The “first 95” represents 95% of people living with HIV knowing their HIV status; the “second 95” represents 95% of people who know their HIV-positive status and are on antiretroviral therapy (ART); and the “third 95” represents 95% of HIV positive people who know their HIV status are on ART and are virally suppressed [1, 4]. At the country and global level, commitment, and resources to meet these indicators has been prioritised as the strategy was expected to prevent onward transmission of HIV and reduce HIV incidence [5, 6, 7].
In 2020, globally, 36 million adults over the age of 15 were living with HIV [4]. Out of these, 84% knew their status, 73% were accessing treatment and 66% were virally suppressed [4]. South Africa contributes approximately 22% of the global HIV burden [4, 8], and KwaZulu-Natal province is the epicentre [9, 10], where the UNAIDS targets has not been met [11, 12]. Whilst South Africa has substantially scaled-up ART provision, having the largest HIV treatment programme globally, has resulted in reducing number of HIV related death [8]. However, country level HIV prevalence (14.0%) with an estimated of 231,100 new infection remains persistently high [13], and almost a fourth of women in their reproductive ages (15–49) were HIV positive at the end of 2020 [8]. KwaZulu-Natal has the highest HIV burden with prevalence of 18.1% compared to Western Cape with a prevalence of 6.8% [14]. Heterosexual sex is the key path to HIV transmission and acquisition in this region [15], where women of reproductive age are disproportionately affected [16, 17], thus increasing the potential of mother to child transmission (MTCT) of HIV during pregnancy, childbirth, or breastfeeding [13, 18]. Thus, viral suppression is critically important among this key population for the prevention of mother-to-child transmission (PMTCT) of HIV [18, 19] and transmission to sexual partners.
Small area location-based approaches have been recommended for targeted interventions, scale up of treatment and identify spatially distributed structural and behavioural risk factors towards achieving the UNAIDS targets and to help to reduce the overall HIV burden [20]. Evidently, their exist geographic variation in the complexity of HIV epidemiological measures [21]. Therefore, spatial analysis and modelling accounting for the presence of spatial autocorrelation between observation and residual must be considered [20, 21]. Failure to account for spatial heterogeneity and possible causes could result in misleading epidemiologist, public health institutions, and policy makers. The national HIV prevalence survey among pregnant women that also examined socioeconomic factors associated with unsuppressed viral load did not account for the possible linear effect of continuous covariates or mapped the spatial effect [22]. Therefore, the aim of this study was to determine factors associated with unsuppressed HIV viral load among women living with HIV while accounting for possible linear effects of some continuous covariates and mapping spatial risk effect using Bayesian inference. Furthermore, study assessed the progress towards UNAIDS indicators, examine the prevalence, and hotspots of unsuppressed HIV viral load among women in a hyperendemic area of KwaZulu-Natal, South Africa. This study applied the Bayesian hierarchical Geoadditive model technique to identify risk factors associated with unsuppressed HIV viral load and mapping the spatial areas in KwaZulu-Natal, South Africa.
This analysis was based on data from HIV Incidence Provincial Surveillance System (HIPSS) that monitored HIV related measures of HIV prevalence and incidence in association with the programmatic scale of HIV prevention and treatment efforts in a “real world” non-trial setting. The study undertook two sequential cross-sectional surveys with the first survey from June 2014 to 18 June 2015 (2014 Survey) and the second survey from 8 July 2015 to 7 June 2016 (2015 Survey). All study participants provided written informed consent and or assent, completed a face-to-face questionnaire to obtain socio-demographic, behavioural, knowledge of HIV testing, sexually transmitted infections (STI) and tuberculosis (TB) history and biological information. From a total of 600 Enumeration Areas (EAs), 591 EAs with more than 50 households were systematically selected at random, of which 221 were drawn for the 2014 Survey and 203 were drawn for the 2015 Survey. Households were randomly selected using multi-stage random sampling, were geo-referenced and one individual per household, within the age range 15–49 years old was randomly selected and invited to participate in the study. In the 2014 Survey a total of 9812 participants were enrolled, of whom 6265 were women, whilst in the 2015 Survey a total of 10,236 participants were enrolled, of whom 6341 were women. All enrolled participants had HIV antibody and viral load testing undertaken. In the 2014 Survey, 2955 were HIV positive and 2946 had viral load measurement, whilst 9 participants had missing viral load measurement. In the 2015 Survey, 2947 women were HIV positive and 2946 had viral load measurements, whilst 1 participant had missing viral load measurement.
HIPSS study was conducted in accordance with the approval by the Biomedical Research Ethics Committee of the University of KwaZulu-Natal (Reference number BF269/13), the KwaZulu-Natal Provincial Department of Health (HRKM 08/14), and the Associate Director of Science of the Centre for Global Health (CGH) at the United States Centre for Disease Control and Prevention (CDC) in Atlanta, United States of America (CGH 2014–080). Details about HIPSS study design, objectives and study and data collection procedures have been described elsewhere [10, 11].
HIPSS was conducted in a geographically defined region of rural Vulindlela and peri urban Greater Edendale areas in the Msunduzi municipality, uMgungundlovu district of KwaZulu-Natal province in South Africa. Whilst this community has basic access to water, electricity and free health facilities, the area is characterised by high rates of unemployment, poverty, and HIV. The EAs are located between 29°39’ South and 30°17 East of KZN, covers a total of 33 wards in the Msunduzi and a part of uMngeni municipalities, in uMgungundlovu district.
The primary outcome variable was HIV viral load status among women living with HIV (WLHIV) in this community, which was categorised as binary outcome:
This threshold was used in accordance with the country revised ART treatment guideline [23, 24] as well as evidence from several studies on transmission potential at this cut off [25, 26]. Unsuppressed viral load calculation and definition was based on the composite viral suppression of all WLHIV irrespective of being on ART or not.
Initial data exploration to identify potential factors associated with unsuppressed viral load was established using multiple correspondence analysis and random forest analysis [27]. The explanatory variables considered in the study comprised of socio-demographic, behavioural, knowledge of HIV status and HIV testing, medical history, and biological variables. These included age, marital status, education level, community duration, migration history, monthly income, accessing health care, meal cut, income loss, place of residence, number of household members, sex last 12 months, number of sexual partners last 12 months, number of total lifetime sex partners, forced first time sex, ever consume alcohol, ever tested for HIV, number of lifetime HIV test, knowledge of HIV status, perceived risk of contracting HIV, exposed to TB last 12 months, ever diagnosed of TB, had any STI symptoms, ever diagnosed of STI, ever pregnant, currently on antiretrovirals (ARV) and current CD4 cell count. The variance inflation factors (VIF) was used to check for collinearity among continuous independent variables and all variables with VIF < 4 was assumed that multicollinearity was not significantly present. Also, non-linear effect of all continuous variables was also examined, of which only age, household size, number of lifetime HIV test and total number of children ever born displayed a significant non-linear effect and were considered in the fitted model while the remaining independent variables were included as linear fixed effect.
To account for the complex multilevel sampling design, weighted percentage and frequency were used to describe and summarise the study characteristics across both surveys. Progress towards each of the 95-95-95 indicators and composite viral suppression was estimated. Comparisons of weighted proportion of viral load status was estimated with associated 95% confidence intervals (CIs) and p values using Taylor series methods. Initial non-spatial bivariate survey logistic regression was used to test association between each background characteristics and the dependent variable using Rao-Scott chi-square test. Statistical analyses were performed using SAS (SAS Institute, Cary, North Carolina) version 9.4. Covariates with significant association at 5% significant level for each study year was included in the multivariate model.
Suppose
Eq. 1 is a semi-parametrical model, where
The argument is that spatial effect is the proxy of most unobserved influence, under which spatial structure assumption must be followed. The structured spatial effect accounts for the assumption that location close in proximity are more likely to be correlated in respect of their outcome. While the unstructured spatial effect accounts for the spatial variation because of the effects of interminable district-level factors that are not related spatially [31, 32, 33].
The study utilised a fully Bayesian inference, hence all parameters and functions were considered as random variables and thus assigned with appropriate prior. Parameter
Where
Independent and identically distributed random variable (i.i.d) Gaussian priors were assigned to the unstructured spatial effect to account for the unobserved covariates that are inherent within the districts, denoted as:
where the variance
Lastly, the posterior distributions of all the parameters
This is a high dimensional model and analysis which sometimes require good knowledge of advance mathematical and statistical computation. So, Markov chain Monte Carlo (MCMC) algorithm is required to generate samples from this distribution which comes with much computational difficulties. To circumvent this problem and difficulties, the Integrated Nested Laplace Approximation (INLA) was used to obtain the estimate [38, 39]. The outmost goal is to estimate marginal posterior distribution for the latent Gaussian model which was used to compute the summary statistics of interest like posterior mean, standard deviation, and 95% credible interval.
Three models were considered for comparison namely:
Deviance information criterion (DIC) of each model were compared. The final Geoadditive model was selected based on smallest DIC which was considered as good predictive performance and best fit model [40, 41]. The summary results give the posterior mean estimates with associated credible interval as well as the spatial effect map. The enumeration area shapefile was created in ArcGIS using the geographic attributes. Bayesian inference was analysed using INLA package in R software [37, 42].
Table 1 shows the sample size and characteristics of HIV positive women in rural and peri urban areas of KwaZulu-Natal, South Africa. Almost half (45.2%) of the women had unsuppressed viral load in 2014 and about one third (38.1%) in 2015. Majority of WLHIV were aged between 20 and 44 years; 86.9% in 2014 and 85% in 2015 with median age and interquartile range (IQR) of 31 [25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38] in 2014 and and 32 [26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40]) years in 2015. Majority of the women were never married; 84.6% in 2014 and 81% in 2015. More than half had incomplete high school education 53.5% in 2014 and 57.3% in 2015. Most women had always lived in the community; 76.5% in 2014 and 54.8% in 2015 whilst never being away from home in the last 12 months was 89.8% in 2014 and 92.7% in 2015. In 2014 75.5% and in 2015, 53.0% of women reported a monthly income of ≤R2500 More than half of women sampled (57.6%) in 2014 were from rural area whilst the majority (63.8%) in 2015 were from urban areas. Overall 77.2% in 2014 and 83.5% in 2015 had engaged in sex in the last 12 months, whilst 46.7% in 2014 and 22.1% in 2015 reported having had two or more number of sex partners in the last 12 months. Overall, the majority; 77.8% in 2014 and 84.3% in 2015 reported having had two or more lifetime sex partners. Almost all the women were not forced to have sex at their first-time sex encounter. Regarding their HIV testing knowledge and perception, 88.9% of women in 2014 and 98.9% in 2015 reported having had an HIV test with 62.7% in 2014 and 69.8% had HIV test more than twice in their lifetime. In 2014, 21.5% had a perception of not likely to contract HIV, while only 14.1% in 2015. Overall, 79.6% of women in 2014 and 88.2% in 2015 had reported having been pregnant in their lifetime. Less than half, 48.8% in 2014 reported to be on ART, though this increased to 59.8% in 2015. More than half of the women 55.8% in 2014 and 58.6% in 2015 had a current CD4 cell counts of ≥500 cells per μL and 23.1% in 2014 and 21.6% in 2015 had CD4 cell counts of <350 per μL.
Characteristics | 2014 Surveyα | 2015 Surveyβ |
---|---|---|
Total | 2955 | 2948 |
Age median (IQR) | 31 [25–37] | 32 [26–39] |
15–19 | 131 (4.6) | 133 (4.9) |
20–24 | 436 (14.3) | 337 (11.2) |
25–29 | 578 (20.3) | 606 (20) |
30–34 | 561 (20.7) | 674 (21.1) |
35–39 | 517 (18.4) | 510 (18.8) |
40–44 | 426(13.2) | 431 (13.9) |
45–49 | 306 (8.5) | 257 (10.2) |
Never married | 2468 (84.6) | 2364 (81) |
Ever married | 478 (15.4) | 584 (19) |
No Schooling | 137 (2.9) | 37 (1.4) |
Incomplete High School | 1525 (53.5) | 1688 (57.3) |
Complete high school | 1293 (43.7) | 1223 (41.2) |
Always | 2290 (76.7) | 1504 (54.8) |
Moved here less than 1 year ago | 88 (2.3) | 122 (3.8) |
Moved here more than 1 year ago | 577 (21.0) | 1322 (41.4) |
Yes | 311 (10.2) | 217 (7.3) |
No | 2644 (89.9) | 2731 (92.7) |
No income | 602 (17) | 50 (1.3) |
≤ R2500 | 2177 (75.5) | 1657 (53.0) |
> R2500 | 169 (7.5) | 1241 (45.8) |
Yes | 682 (24.5) | 1477 (50.8) |
No | 2273 (75.5) | 1469 (49.2) |
Yes | 606 (22.1) | 1330 (46.2) |
No | 2342 (77.9) | 1616 (53.8) |
Yes | 1216 (44.9) | 2168 (73.3) |
No | 1732 (55.1) | 778 (26.7) |
Rural | 1009 (57.6) | 954 (36.2) |
Urban | 1946 (42.4) | 1994 (63.8) |
Yes | 2218 (77.2) | 2501 (83.5) |
No | 737 (22.8) | 447 (16.5) |
1 partner | 1178 (53.3) | 1824 (72.9) |
2 or more partners | 1034 (46.7) | 677 (27.1) |
1 partner | 533 (22.2) | 455 (15.7) |
2 or more partners | 1844 (77.8) | 2429 (84.3) |
No response | 879 | 64 |
Yes | 72 (2.5) | 100 (3.3) |
No | 2831 (95.9) | 2833 (96.1) |
Do not remember | 52 (1.6) | 15 (0.5) |
Yes | 390 (11.5) | 536 (18.5) |
Never | 2564 (88.5) | 2412 (81.5) |
Yes | 2513 (88.9) | 2868 (96.9) |
No | 442 (11.1) | 80 (3.1) |
Never | 442 (11.1) | 81 (3.1) |
1 time | 769 (26.2) | 765 (27.1) |
2 or more times | 1744 (62.7) | 2102 (69.8) |
Yes | 1870 (65.6) | 2219 (73.7) |
No | 1085 (34.4) | 729 (25.3) |
Likely to acquire HIV | 573 (19.3) | 461 (16) |
Not likely to acquire HIV | 686 (21.5) | 405 (14.1) |
I am already infected | 1696 (59.2) | 2082 (70) |
103 (3.6) | 162 (5.9) | |
2853 (96.6) | 2786 (94.1) | |
Yes | 251 (9.6) | 363 (12.7) |
No | 2704 (90.4) | 2585 (87.3) |
Yes | 219 (9.0) | 449 (14.9) |
No | 2736 (91.0) | 2499 (85.1) |
Yes | 1245 (47.1) | 1689 (57.4) |
No | 1710 (52.9) | 1259 (42.6) |
Yes | 163(4.5) | 80(2.9) |
No | 2792(95.5) | 2868(97.1) |
Yes | 213 (9.1) | 320 (11.3) |
No | 2742 (90.9) | 2628 (88.7) |
Yes | 2346 (79.6) | 2595 (88.1) |
No | 600 (20.4) | 353 (11.9) |
Yes | 1346 (48.8) | 1775 (59.8) |
No | 1600(51.2) | 1172 (40.2) |
Single/fixed | 1079 (86.3) | 1580 (88.5) |
Multiple | 172 (13.7) | 196 (11.5) |
<350 cells per μL | 696 (23.1) | 634 (21.7) |
350–499 cells per μL | 639 (21.1) | 576 (19.7) |
≥500 cells per μL | 1593 (55.8) | 1729 (58.6) |
Characteristics of HIV positive women in Vulindlela and Greater Edendale, KwaZulu-Natal, South Africa, 2014–2015.
Participants missing for: a = 7, and f = 27 in 2014; b, c and d = 2, f = 9 in 2015. No response: e: = 879(64) for 2014(2015). Missing data were excluded from percentage calculation. ZAR = South African Rand (ZAR15 ∼ US$1). TB = tuberculosis, STI = sexually transmitted infections, ARV = antiretroviral drugs, ART = antiretroviral therapy, Ever had any STI symptoms = any symptoms of abnormal vaginal discharge, burning or pain when passing urine or presence of any genital warts/ulcers.
Figure 1 provides the status on the UNAIDS 95–95-95 indicators. Of the 2955 women in 2014 and 2948 in 2015 who tested positive for HIV, 9 and 1 participants respectively had no viral load measurement. Thus, 2946 women in 2014 and 2947 women in 2015 had viral load measurements. In 2014, to meet the “first 95”, 65.5% (95% CI, 62.9–68.2) (n = 1890/2955) were aware of their HIV positive status and for the “second 95”, 74.2% (95% CI, 71.6–76.8 (n = 1348/1870) had initiated ART and for the “third 95”, 82.9% (95% CI, 80.4–85.4) (n = 1105/1346) had achieved viral suppression, and overall viral suppression among all HIV positive women was 54.8% (95% CI, 52.0–57.5) (n = 1574/2946). While in 2015, progress towards 95–95-95 targets were: 74.7% (95% CI, 72.7–76.6) (n = 2219/2948) were aware of their HIV status; 80.0% (95% CI, 78.1–82.0) (n = 1777/2219) of these had initiated ART and 88.2% (95% CI, 86.6–89.9) (n = 1551/1777) of those on ART had achieved HIV viral suppression, resulting in the overall viral suppression among all HIV positives to be 61.9% (95% CI, 59.7–64.1) (n = 1828/2947).
Progress of the UNAIDS 95–95-95 indicators by age group and overall, among HIV positive women (2014–2015). (A). First 95: Women living with HIV who know they are HIV positive. (B). Second 95: Women who knew they were HIV positive and were taking ART. (C). Third 95: Women who knew their HIV positive, were on ART and had achieved HIV viral suppression at HIV viral load <400 copies/ml. (D). UNAIDS composite measure towards achieving HIV viral suppression among all HIV positive women.
Disaggregated by age groups, Figure 1a shows the progress towards the “first 95” Knowledge of HIV status increased from 65.6% in 2014 to 74.7% in 2015, and across age groups, with highest achieved among 35–39 (86.5%), 40–44 (82.4%) and 45–49 (82.4%) in 2015. Highest increase in the knowledge of HIV positive status was in the age group 15–29, increasing from 25.8% in 2014 to 46.7% in 2015. Figure 1b shows the progress towards the “second 95”. Overall proportion of women who knew their HIV positive status and were on ART increased from 74.2% in 2014 to 80.0% in 2015. The uptake of ART varied across age groups, uptake was high in the 15–19 years age group at 74.8% in 2014 and 75.9% in 2015; in ages 30–34 uptake was 77.2% in 2014 and 80.5 in 2015; in ages 35–39 years uptake was 77.8% in 2014 and 85.6% in 2015; in ages 40–44 years uptake was 77.1% in 2014 and 84.6% in 2015 and in age 45–49 uptake was 79.1% in 2014 and 84.2% in 2015. However, ART uptake in the age group 20–24 years was lowest at 62.4% in 2014 and 62.8% in 2015. Figure 1c shows the progress towards the “third 95”, that is the proportion of HIV positive women who knew their HIV positive status, were on sustained ART and who had achieved viral suppression of <400 copies per mL. Proportion varied across ages group; HIV viral suppression was lowest at 66% among 20–24 years old in 2014 and increased to 74.4% in 2015. Viral suppression of 92.9% was achieved among 45–49 years old and 91.7% among 40–44 years old and 91.8% among 35–39 years old in 2015. Figure 1d shows the overall UNAIDS 95–95-95 composite measure of achieving viral suppression of 86% among all HIV positive women. Overall, 54.8% of women in 2014 and 61.9% in 2015 had achieved HIV viral suppression of <400 copies per mL. Substantial variation existed across the age groups, with 27% among 15–19 years in 2014 and increased to 46% in 2015. Highest achievement was observed with 76% among 45–49 years old.
Table 2 shows the overall prevalence of unsuppressed HIV viral load was 45.2% (95 CI, 42.5–48.0), (n/N = 1372/2946) in 2014 and 38.1% (95% CI, 35.9–40.3), (n/N = 1119/2947) in 2015. Viral suppression increased by 7.1% over the study period with high viral load prevalence decreasing as age increased and it was 72.9% (95% CI, 62.7–83.2), (n = 95/130) in 15–19 years age group, 68.2% (95% CI, 62.4–73.9), (n = 290/433) in the 20–24 years age group, 47.3% (95% CI, 41.9–52.7), (n = 299/577) in 25–29 years age group, 43.1% (95% CI, 37.9–48.3), (n = 248/561) in 30–34 years age group, 32.5% (95% CI, 26.6–38.4), (n = 185/513) in 35–39 years age group, 36.5% (95% CI, 30.6–42.4), (n = 153/426) in 40–44 years age group, 33.0% (95% CI, 26.6–39.3), (n = 102/306) in 45–49 years age group. In 2015, prevalence also decreased by age and it was 56.0% (95% CI, 43.8–64.1), (n = 74/133); 65.1 [59.5–70.7], (n = 210/337); 46.5 [41.4–51.5], (n = 279/606); 36.4% (95% CI, 32.1–40.8), (n = 244/674); 25.2% (95% CI, 20.9–29.4), (n = 125/509); 29.1% (95% CI, 24.0–34.2), (n = 120/431); 24.0% (95% CI, 18.3–29.8), (n = 67/257) in the 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49 years age categories (
Characteristics | 2014 Survey | 2015 Survey | ||||
---|---|---|---|---|---|---|
≥400 copies per mL | 1372/2946 | 45.2 [42.5–48.0] | 1119/2947 | 38.1 [35.9–40.3] | ||
<400 copies per mL | 1574/2946 | 54.8 [52.0–57.5] | 1828/2927 | 61.9 [59.7–64.1] | ||
Age median (IQR) | 31 [26–39] | 32 [26–39] | ||||
Socio-demographic characteristics | ||||||
Age groups (years) | ||||||
15–19 | 95/131 | 72.9 [62.7–83.2] | <0.0001 | 74/133 | 56.0[43.8–64.1] | <0.0001 |
20–24 | 290/433 | 68.2 [62.4–73.9] | 210/337 | 65.1 [59.5–70.7] | ||
25–29 | 299/577 | 47.3 [41.9–52.7] | 279/606 | 46.5 [41.4–51.5] | ||
30–34 | 248/561 | 43.1 [37.9–48.3] | 244/674 | 36.4 [32.1–40.8] | ||
35–39 | 185/513 | 32.5 [26.6–38.4] | 125/509 | 25.2 [20.9–29.4] | ||
40–44 | 153/426 | 36.5 [30.6–42.4] | 120/431 | 29.1 [24.0–34.2] | ||
45–49 | 102/306 | 33.0 [26.6–39.3] | 67/257 | 24.0 [18.3–29.8] | ||
Never married | 1188/2468 | 46.4 [43.6–49.2] | 0.03 | 948/2364 | 40.6 [38.1–43.2] | <0.0001 |
Ever married | 184/478 | 39.0 [32.3–45.6] | 171/583 | 27.4 [23.4–31.4] | ||
No schooling | 63/137 | 44.1 [34.8–53.4] | 0.09 | 10/37 | 30.2 [12.8–47.6] | 0.03 |
Incomplete High School | 672/1521 | 43.2 [39.3–47.0] | 605/1688 | 35.7 [32.8–38.6] | ||
Complete High School | 637/1288 | 47.9 [44.4–51.4] | 504/1222 | 41.7 [38.0–45.3] | ||
Always | 1078/2282 | 45.5 [42.7–48.4] | 0.53 | 585/1504 | 39.0 [35.8–42.1] | 0.04 |
Moved here less than 1 year ago | 44/88 | 48.4 [34.3–62.4] | 60/122 | 48.4 [38.1–58.7] | ||
Moved here more than 1 year ago | 250/576 | 43.9 [38.3–49.5] | 474/1321 | 36.0 [33.1–39.0] | ||
Yes | 152/311 | 50.1 [41.9–58.3] | 0.21 | 113/217 | 50.2 [42.6–57.7] | 0.01 |
No | 1220/2635 | 44.7 [41.9–47.5] | 1006/2730 | 37.2 [34.9–39.4] | ||
No income | 285/601 | 46.4 [41.0–51.7] | 0.29 | 17/50 | 34.4 [19.8–49.0] | 0.89 |
≤R2500 | 1017/2170 | 45.6 [42.4–48.8] | 627/1656 | 38.0 [35.3–40.7] | ||
> R2500 | 67/168 | 38.8 [30.2–47.4] | 475/1241 | 38.3 [34.9–41.7] | ||
Yes | 318/682 | 47.0 [41.2–52.7] | 0.04 | 549/1477 | 37.7 [34.7–40.8] | 0.02 |
No | 1051/2257 | 44.7 [41.8–47.5] | 569/1468 | 38.5 [35.4–41.6] | ||
Yes | 285/606 | 47.4 [41.5–53.3] | 0.38 | 499/1330 | 37.3 [34.0–40.5] | 0.45 |
No | 1084/2333 | 44.6 [41.8–47.5] | 619/1615 | 38.8 [35.9–41.7] | ||
Yes | 488/1212 | 41.7 [37.4–46.0] | 0.03 | 769/2167 | 35.5 [33.0–38.1] | <0.0001 |
No | 881/1727 | 48.1 [44.4–51.8] | 349/778 | 45.2 [41.2–49.2] | ||
Rural | 457/1006 | 44.5 [40.3–48.7] | 0.51 | 340/954 | 36.3[32.1–40.4] | 0.25 |
Urban | 915/1940 | 46.2 [43.4–49.1] | 779/1993 | 39.1 [36.7–41.7] | ||
Yes | 1052/2212 | 45.8 [42.8–48.8] | 0.29 | 965/2501 | 38.8[36.4–41.3] | 0.14 |
No | 320/734 | 43.3 [38.9–47.7] | 154/446 | 34.4[28.9–39.8] | ||
1 partner | 908/1178 | 46.1 [43.0–49.2] | 0.02 | 860/1824 | 38.2[35.6–40.7] | 0.03 |
2 or more partners | 464/1034 | 43.6 [39.1–47.4] | 259/677 | 37.9[33.6–42.3] | ||
1 partner | 265/532 | 48.3 [42.0–54.6] | 0.01 | 185/455 | 39.4[34.7–44.1] | 0.05 |
2 or more partners | 828/1839 | 43.7 [40.7–46.8] | 910/2428 | 37.9[354–40.2] | ||
Yes | 31/72 | 38.8 [26.1–51.5] | 0.28 | 33/100 | 34.7[23.7–45.7] | 0.74 |
No | 1314/2822 | 45.2 [42.4–48.0] | 1082/2832 | 38.3[36.0–40.6] | ||
Do not remember | 27/52 | 56.1 [39.4–72.9] | 04/15 | 30.4[1.1–59.7] | ||
Yes | 229/390 | 58.8 [51.7–65.9] | <0.0001 | 249/536 | 44.4[39.4–49.5] | <0.0001 |
No | 1143/2556 | 43.9 [40.6–46.3] | 870/2411 | 36.6[34.2–39.1] | ||
Yes | 1086/2505 | 42.4 [39.5–45.3] | <0.0001 | 1066/2867 | 37.3[35.1–39.5] | <0.0001 |
No | 286/441 | 68.1 [63.2–73.0] | 53/80 | 63.4[51.4–75.4] | ||
Yes | 619/1865 | 31.2 [28.1–34.3] | <0.0001 | 591/2218 | 25.8[23.6–28.0] | <0.0001 |
No | 753/1081 | 72.0 [68.5–75.6] | 528/729 | 74.3[70.7–77.8] | ||
Likely to Acquire HIV | 364/572 | 67.4 [62.1–72.6] | <0.0001 | 309/461 | 69.0[64.0–74.0] | <0.0001 |
Not likely to Acquire HIV | 478/682 | 70.7 [66.1–74.7] | 281/405 | 70.2 [64.8–75.5] | ||
I am already infected | 530/1692 | 28.9 [25.8–31.9] | 529/2081 | 24.6[22.3–26.9] | ||
Never | 286/441 | 68.1 [63.2–73.0] | <0.0001 | 54/81 | 63.7[51.8–75.6] | <0.0001 |
1 time | 330/764 | 41.6 [37.1–46.2] | 225/765 | 29.1[25.2–33.1] | ||
2 or more times | 756/1741 | 42.7 [39.1–46.3] | 840/2101 | 40.4[37.7–43.2] | ||
Yes | 41/102 | 41.2 [27.8–54.6] | 0.56 | 44/159 | 22.4[14.9–29.9] | <0.0001 |
No | 1331/2844 | 45.4 [42.6–48.2] | 1075/2786 | 39.0[36.8–41.3] | ||
Yes | 77/251 | 30.9 [23.2–38.6] | <0.0001 | 82/362 | 19.7[15.6–23.9] | <0.0001 |
No | 1295/1295 | 46.8 [44.0–49.5] | 1037/2585 | 40.8[38.4–43.2] | ||
Yes | 48/217 | 20.6 [13.6–27.6] | <0.0001 | 84/449 | 16.7[12.7–20.7] | <0.0001 |
No | 1324/2729 | 47.6 [45.0–50.3] | 1035/2498 | 41.8[39.4–44.3] | ||
Yes | 417/1242 | 32.6 [28.8–36.4] | <0.0001 | 463/1688 | 27.1[24.7–29.5] | <0.0001 |
No | 955/1704 | 56.5 [53.4–59.6] | 656/1259 | 52.9[49.5–56.3] | ||
Yes | 65/162 | 37.3 [28.1–46.4] | 0.08 | 30/80 | 37.4[23.0–51.9] | 0.92 |
No | 1307/2784 | 45.6 [42.9–48.4] | 1089/2867 | 38.1[35.8–40.4] | ||
Yes | 98/213 | 43.7 [35.0–52.4] | 0.71 | 155/320 | 47.7[41.5–53.9] | 0.001 |
No | 1274/2733 | 45.4 [42.5–48.3] | 964/2627 | 36.9[34.5–39.3] | ||
Yes | 1029/2346 | 42.5 [39.6–45.5] | <0.0001 | 947/2595 | 36.6[34.3–38.9.5] | <0.0001 |
No | 343/596 | 59.4 [53.7–65.1] | 169/352 | 49.3[42.6–55.9] | ||
Yes | 241/1346 | 17.1 [14.6–19.6] | <0.0001 | 220/1775 | 11.8[10.2–13.5] | <0.0001 |
No | 1131/1600 | 72.1 [68.9–75.3] | 899/1172 | 77.3[74.4–80.2] | ||
Single/fixed | 127/1077 | 11.5 [8.9–14.0] | <0.0001 | 170/1579 | 24.4(17.1–31.7) | <0.0001 |
Multiple | 36/172 | 21.2 [12.3–30.1] | 50/196 | 10.2(8.9–11.7) | ||
<350 per μL | 493/695 | 69.3 [64.8–73.8] | <0.0001 | 430/633 | 68.5[64.4–72.5] | <0.0001 |
350–499 per μL | 315/638 | 49.1 [43.2–55.0] | 247/576 | 42.0[37.4–46.6] | ||
≥500 per μL | 546/1591 | 33.2 [29.9–36.5] | 437/1729 | 25.6[23.2–28.0] |
Prevalence of unsuppressed viral load by study characteristics among women in Vulindlela and Greater Edendale, KwaZulu-Natal, South Africa, 2014–2015.
A total of nine women in 2014 survey and one woman in 2015 survey were missing viral load data. Participants missing for: a = 7, and e = 27 in 2014; b, c and d = 2, e = 9 in 2015.
Whilst unsuppressed viral load prevalence was similar across most variables decrease in the trends over the study years was observed. In 2014 unsuppressed viral load prevalence was 50.1%, (n = 152/311) and declined to 20.2%, n = 113/217) in 2015, among women that were away from home in the last 12 months (compared to those that were never away from home; 44.7%, (n = 1220/2635) in 2014 and 37.2%, n = 1006/2730) in 2015. Among those that ever-consumed alcohol 58.8%, (n = 229/390) in 2014 and declined to 44.4%, n = 249/536) in 2015 compared to those that never consumed alcohol and 43.9%, (n = 1143/2556) (36.6%, n = 870/2411) also among those that never had HIV test 68.1%, (n = 286/441) (63.4%, n = 53/80). Among those that ever had an HIV test 42.4%, (n = 1086/2505) in 2014 and 37.3%, n = 1066/2867) in 2015 had unsuppressed viral load. Similarly, among women who did not know their HIV status 72.0%, (n = 753/1081) in 2014 and 74.3%, (n = 528/729) in 2015 compared to those who knew their status 31.2%, (n = 619/1875) in 2014 and 25.8%, n = 591/2218) in 2015 had unsuppressed viral load. Women who perceived they are not likely to contact HIV 70.7%, (n = 478/682) in 2014 and 70.2% (n = 281/405) in 2015 compared to those who already perceived they had been infected 28.9%, (n = 530/1692) (24.6%, n = 529/2081), also women who have ever been diagnosed of STI 43.7%, (n = 98/213) (47.7%, n = 155/320), among women who had never been pregnant 59.4%, (n = 343/600) (49.3%, n = 169/352) compared to those that has ever been pregnant 42.5%, (n = 1029/2346) (36.6%, n = 947/2595), likewise among WLHIV and not on ART 72.1% (n = 1131/1600) (77.3%, n = 899/1172) in comparison with those on ART 17.1% (n = 241/1346) (11.8%, n = 220/1775). Prevalence was higher among women whose current CD4 cell count were < 350 count per μ/L, 69.3%, (n = 493/695) (68.5%, n = 430/633), and those with CD4 cell count of between 350 and 499 count per μ/L 49.1%, (n = 315/638) (42.0%, n = 247/576) compared to those 500 count per μ/L 33.2%, (n = 546/1591) (25.6%, n = 437/1729) in 2014(2015) respectively.
Figure 2 shows the observed prevalence map of unsuppressed viral load. Highest prevalence was observed in the north and south of Vulindlela and east part of Greater Edendale in 2014, while in the north part of Vulindlela and the south part of Greater Edendale in 2015. The north area (Mpophomeni) showed a consistently high prevalence across both surveys.
Observed prevalence maps of unsuppressed viral load among women (a) 2014 and (b) 2015 in Vulindlela and Greater Edendale area in uMgungundlovu district, KwaZulu-Natal province, South Africa.
Table 3 shows values of the deviance information criterion (DIC) and effective numbers of parameters (pD) for each of the fitted model. Unstructured model has the minimum values (DIC = 2593.26 and 2087.70) for 2014 and 2015 respectively, thus attesting as the best fit model for the data sets, while GAM model offers the least fit. Besides, the unstructured model is of actual interest because it contains all the variables considered, and account for spatial autocorrelation and between clusters heterogeneity, failure to do so would have produced misleading and overfitting results. Thus, further results of this study are based on the unstructured model.
2014 Survey | 2015 Survey | |||||
---|---|---|---|---|---|---|
DIC | 2768.42 | 2597.64 | 2593.26 | 2097.27 | 2089.95 | 2087.70 |
DIC saturated | 2998.34 | 2992.52 | 3004.69 | 2992.61 | 2987.95 | 2998.66 |
44.92 | 48.88 | 49.23 | 46.53 | 46.50 | 47.55 |
Model diagnostic.
DIC: Deviance Information Criteria. pD: effective numbers of parameters.
Figure 3 shows the non-linear effect of continuous covariates after accounting for other variables. The results shows that current age, number of household members, total number of children ever born and total number of lifetime HIV test, had a non-linear significant effect on women being virally unsuppressed in this study area. Furthermore, in Figure 3a and e shows a slight increase in effect among ages 15 to 20 in 2014 and sharp increase in 20 to 25 in 2015, after which the effect declined. Younger age 15 to 29 have higher risk of being virally unsuppressed compared to ages 30 above. Figure 3b and f shows that risk of unsuppressed viral load decreases with higher number of household members from 5 members. Also Figure 3c and h shows that the effect of total number of children ever born decreases the risk of being virally unsuppressed in 2014 but increases in 2015. Similarly, Figure 3d and g showed that the risk of unsuppressed viral load increased as the number of lifetime HIV tests increased in 2014, whilst in contrast unsuppressed viral load decreased as the number of lifetime HIV tests increased in 2015.
Nonlinear effect of continuous covariate.
Table 4 displays the adjusted posterior mean estimates with their 95% credible intervals of the linear fixed effect from the multivariable model. If these intervals contain the number zero (0), then the parameter (estimate of the mean beta) is not significant; otherwise, it is significant. Factors associated with unsuppressed viral load across both years were knowledge of HIV status, low perceived risk of contracting HIV, ARV treatment and current CD4 cell counts. Women with no prior knowledge of their HIV status were more likely to be virally unsuppressed than those that knew their status. Women with either unlikely or likely perception of contracting HIV, not on ARV, and for those on ARV having multiple tablets of ARV had the highest risk of being virally unsuppressed compared to their reference categories. Additionally, in 2014 those that ever consumed alcohol were also at higher risk of having unsuppressed viral load. While in 2015, we also found that women that reported being away from home in the last 12 months, had a meal cut, being with two or more sexual partners in one’s lifetime, ever tested with TB and ever diagnosed with STI had the highest risk of being virally unsuppressed compared to their counterparts.
2014 Survey | 2015 Survey | |||||
---|---|---|---|---|---|---|
Variables | Posterior mean | Posterior SD | 95 Credible intervals | Posterior mean | Posterior SD | 95% credible intervals |
0.405** | 0.075 | (0.255, 0.551) | 0.407** | 0.076 | (0.257, 0.557) | |
Never married | 0.032 | 0.017 | (−0.002, 0.067) | 0.005 | 0.021 | (−0.035, 0.045) |
Incomplete high school | 0.015 | 0.021 | (−0.015, 0.045) | −0.005 | 0.014 | (−0.032, 0.022) |
Moved here less than 1 year ago | −0.016 | 0.042 | (−0.099,0.068) | 0.044 | 0.033 | (−0.022, 0.109) |
Moved here more than 1 year ago | 0.002 | 0.019 | (−0.034, 0.039) | 0.002 | 0.014 | (−0.025, 0.029) |
Yes | 0.002 | 0.024 | (−0.045, 0.048) | 0.056 | 0.025 | (0.007, 0.105) |
Yes | 0.016 | 0.026 | (−0.035, 0.067) | 0.011 | 0.018 | (0.024, 0.045) |
No | 0.018 | 0.016 | (−0.013, 0.049) | 0.014 | 0.015 | (−0.016, 0.044) |
2 or more partners/no res | 0.024 | 0.019 | (−0.013, 0.061) | 0.002 | 0.019 | (−0.036, 0.039) |
2 or more partners | 0.037 | 0.027 | (−0.016, 0.091) | 0.049 | 0.058 | (0.102, 0.162) |
Yes | 0.058 ** | 0.022 | (0.016, 0.101) | 0.029 | 0.017 | (−0.005, 0.063) |
No | −0.058 | 0.034 | (−0.120, 0.014) | −0.022 | 0.045 | (−0.110, 0.066) |
No | −0.142 | 0.030 | (−0.201, −0.084) | −0.200 | 0.030 | (−0.259, −0.142) |
Likely | 0.095 | 0.025 | (0.045, 0.144) | 0.062 | 0.028 | (0.008, 0.116) |
Not Likely | 0.103 | 0.027 | (0.050, 0.156) | 0.074 | 0.029 | (0.017, 0.131) |
Yes | −0.034 | 0.018 | (−0.069, 0.001) | −0.070 | 0.015 | (−0.099, −0.041) |
Yes | 0.061 | 0.041 | (−0.019, 0.142) | −0.022 | 0.029 | (−0.079, 0.035) |
Yes | 0.008 | 0.028 | (−0.048, 0.064) | 0.005 | 0.022 | (−0.038, 0.048) |
Yes | −0.052 | 0.029 | (−0.108, 0.004) | −0.027 | 0.019 | (−0.064, 0.010) |
Yes | 0.034 | 0.033 | -(0.031, 0.100) | −0.077 | 0.039 | (−0.084, 0.069) |
Yes | 0.042 | 0.028 | (−0.014, 0.097) | 0.059 | 0.021 | (0.018, 0.099) |
No | −0.065 | 0.019 | (−0.103, 0.028) | 0.001 | 0.018 | (−0.156, 0.059) |
No | 0.321** | 0.030 | (0.262, 0.379) | 0.511 | 0.031 | (0.451, 0.571) |
Multiple | 0.251** | 0.027 | (0.199, 0.303) | 0.242 | 0.018 | (−0.163, −0.093) |
350–499 | −0.184 | 0.021 | (−0.226, −0.143) | −0.157 | 0.020 | (−0.197, −0.118) |
≥ 500 | −0.319 | 0.018 | (−0.354, −0.285) | −0.287 | 0.016 | (−0.319, −0.254) |
Adjusted posterior means, standard deviation (SD) and 95% credible intervals for the best fitted model.
Significant at 5% level of significance.
Figure 4 shows the chloropleth spatial effect maps based on model 3, shows both positive and negative effects with predicted high and low risk areas of unsuppressed viral load. The colours on the chloropleth maps show the log-odds scale, indicating each area contribution to the odds of unsuppressed viral load in women. Predicted high risk areas are shaded in yellow and gold brown (0.00015 to 0.00020), in 2014, two distinct locations were in the north-east and south-west, while 2015 shows a clustered area in the south-east. Predicted lower risk areas are shaded in royal to dark blue (−0.00015 to −0.00025), the south-west in 2014, with both north and west in 2015. Evidently their exist spatial variation of unsuppressed viral load in this hyperendemic community.
Estimated posterior mean of the unstructured spatial effect map on the log-odds of unsuppressed viral load among women in uMgungundlovu district, KwaZulu-Natal province, South Africa (2014–2015). (a) 2014, (b) 2015.
This analysis examined factors associated with unsuppressed viral load among women ages 15–49 years in peri-urban Greater Edendale and rural Vulindlela areas in the uMgungundlovu district, KwaZulu-Natal, South Africa between 2014 to 2015 while accounting for possible nonlinear effect of some continuous variables and mapping the unstructured spatial effects. We fitted hierarchical Bayesian Geoadditive multivariate model while controlling for the confounding effects of the explanatory variables. Bayesian spatial approach have numerous advantages over frequentist statistics, such as ability to account for and measure uncertainty in a model, minimise bias in complex data, ability to produce smoothed risk map, increased prediction accuracy, just to name a few [39, 43, 44]. Due to the strength of this approach many studies have emanated in investigating risk factors of anaemia in Sub Saharan Africa [33, 45], of HIV variation in Kenya [32], viral suppression [46] and other infectious disease globally [47]. Application of Bayesian spatial modelling therefore helped in identifying predictors and high-risk location of unsuppressed viral load among women in a small enumeration area. This enhancement of strategically identifying areas of key population is highly recommended as part of the global AIDS strategy to end inequality in resources allocation and provide localised HIV intervention in hyperendemic communities.
Our study found that knowledge of HIV status, perceived risk of contracting HIV, not on ART, and ART dosage were consistent significant factors associated with higher odds of being virally unsuppressed across both years. Having a CD4 cell count of >350 cells per μL was more likely to be associated with viral load <400 copies per mL Additionally, alcohol consumption was significant in 2014 while meal cut, total number of lifetime sex partner, ever tested for TB and ever diagnosed with STI were factors associated with unsuppressed viral load in 2015. These revealed the heterogeneity and need for continuous surveillance of HIV and its measures, as the predictors of this outcome are dynamic. Although fewer studies on women have been conducted in the country and other developing countries. Similar findings on the association of higher number of sexual partners were also reported among women in uMkhanyakude district of north KZN [48]. The use of ART and dosage of ARV was also found to be significant which is similar to past studies [49, 50]. Furthermore, similar studies have found higher CD4 cell count of >350 cells per μL to be predictive of being virally unsuppressed [51, 52]. We also found similar results on alcohol [53] from Western cape, South Africa and history of TB or STI in Kenya and Uganda [49, 54]. Alcohol use has been found to be associated with non-adherence to treatment in people living with HIV [55] and prevalence of which leads to high risk of transmission [56]. Several studies have shown relationship between TB and virological non-suppression [51, 57]. Similarly, concurrent ART and TB/STI treatment has been shown to increase the risk of virological non-suppression due to impaired treatment adherence and pharmacokinetics drug interaction [49].
The nonlinear effects of age, household size, total number of children ever born and total lifetime HIV test were considered. Across both years, risk of being virally unsuppressed decreases as age increases, with younger age 15–20 having a higher risk and being older associated with reduced risk of unsuppressed viral load. This is similar to past studies [48, 58]. Also risk of being virally unsuppressed decreases with increasing size of the family. Having 5 or lower number of family member showed a higher risk of being unsuppressed. This revealed that larger family members could bring more support to WLHIV. In contrast unsuppressed viral load decreases as number of children ever born increases in 2014 while the inverse was observed in 2015 (risk increases as number of birth increases). Recent study among pregnant women revealed significant association of currently breastfeeding with increase odd of viral load non-suppression [22, 59].
The unstructured spatial effect and observed prevalence map revealed the existence of localised positive spatial variation of unsuppressed viral load among women of reproductive age in this hyperendemic community. While higher prevalence was observed in the north area from both surveys and southern area in 2015. The predicted risk map revealed that in 2014 north-east and south-west as well as south-west in 2015 have an increase likelihood of being virally unsuppressed. This evidently shows that there are regional/district specific factors contributing to unsuppressed viral load with substantial spatial variation. Spatial variation in HIV and its measures has been reported by previous studies [16].
Among women in this community progress on 95–95-95 target was 65.5%, 74.2%, 82.9% in 2014 and 74.7%, 80.0%, 86.6% in 2015. The largest shortfall was in the first target, which is the entry point to health care system. None of the UNAIDS targets were met among this key population. Although, the country has made significant progress but has not achieved the UNAIDS 95–95-95 and 86% composite viral suppression target [14]. However, significant increase in viral suppression of 7.1% over a one year period was seen in this study, while ages 35 to 49 contributed to this increase, which could be attributed to the country commitment and effort in ART scaleup and intervention [27]. However, judging by the 90–90-90 indicator, our findings showed that the “third 90” target was met among age group 35–39, 40–44, 45–49 (91.8%, 91.7%, 92.9%) in 2015.
The key strengths of our study were the robustness of the study design, high participation rate, available of spatial variables and conducting the survey in a real time setting.
This was a cross sectional population based study and not a randomised clinical trial with limited ART data available. Therefore, no causal effect could be established between unsuppressed viral load and women characteristics. The results are not generalisable to older individuals or children as study only accessed men and women aged 15–49 years.
Spatial effects in the model act as a representative of the unobserved predictors which strengthen the result. Identifying high risk areas could help policy maker, epidemiologist, and public health institutions to develop develop strategies and interventions that are suitable for women in the area, thus increasing the impact of allocated resources as well as effective monitoring to improve the health status of women in the community. Increase in progress of the 95–95-95 targets over time showed that the target is achievable in this community among this key population, with intensive HIV testing service, eradication of stigmatisation, ending inequality and increasing uptake of ART treatment. Knowledge of HIV status is a proxy and entry point to achieving the other indicators, generally women are more likely to test than men and receive optimum health care especially during pregnancy.
The likelihood of being virally unsuppressed was higher among younger age group, highlighting public health implication of sustained risk of HIV transmission. Aside clinical factors, family support cannot be underestimated as part of the factors that could help in achieving undetectable viral load among women of reproductive age. Right perception and knowledge of HIV positive status, being on ART and having a higher CD4 cell count contributed to achieving viral suppression. Thus, these remain multi-factorial and important public health priority to attain viral suppression towards the goal to end the epidemic by 2030.
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Perveen"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8929",title:"Modern Beekeeping",subtitle:"Bases for Sustainable Production",isOpenForSubmission:!1,hash:"cbf5aca68ed2c6690ad99f68aaaddcaf",slug:"modern-beekeeping-bases-for-sustainable-production",bookSignature:"Ramón Eduardo Rebolledo Ranz",coverURL:"https://cdn.intechopen.com/books/images_new/8929.jpg",editedByType:"Edited by",editors:[{id:"193813",title:"Dr.",name:"Ramón Eduardo",middleName:null,surname:"Rebolledo Ranz",slug:"ramon-eduardo-rebolledo-ranz",fullName:"Ramón Eduardo Rebolledo Ranz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7561",title:"Beekeeping",subtitle:"New Challenges",isOpenForSubmission:!1,hash:"1c47c831256fe10ff19fb10f490930fc",slug:"beekeeping-new-challenges",bookSignature:"Ramón Eduardo Rebolledo Ranz",coverURL:"https://cdn.intechopen.com/books/images_new/7561.jpg",editedByType:"Edited by",editors:[{id:"193813",title:"Dr.",name:"Ramón Eduardo",middleName:null,surname:"Rebolledo Ranz",slug:"ramon-eduardo-rebolledo-ranz",fullName:"Ramón Eduardo Rebolledo Ranz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6619",title:"Insect Science",subtitle:"Diversity, Conservation and Nutrition",isOpenForSubmission:!1,hash:"08241b041b2072a88452041f8fdebe7e",slug:"insect-science-diversity-conservation-and-nutrition",bookSignature:"Mohammad Manjur Shah and Umar Sharif",coverURL:"https://cdn.intechopen.com/books/images_new/6619.jpg",editedByType:"Edited by",editors:[{id:"94128",title:"Dr.",name:"Mohammad Manjur",middleName:null,surname:"Shah",slug:"mohammad-manjur-shah",fullName:"Mohammad Manjur Shah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5163",title:"Beekeeping and Bee Conservation",subtitle:"Advances in Research",isOpenForSubmission:!1,hash:"fc469ff4d2cf6651cfdbf3c5cf90a469",slug:"beekeeping-and-bee-conservation-advances-in-research",bookSignature:"Emerson Dechechi Chambo",coverURL:"https://cdn.intechopen.com/books/images_new/5163.jpg",editedByType:"Edited by",editors:[{id:"94059",title:"Dr.",name:"Emerson",middleName:"Dechechi",surname:"Dechechi Chambó",slug:"emerson-dechechi-chambo",fullName:"Emerson Dechechi Chambó"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:5,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"50073",doi:"10.5772/62487",title:"Impacts of Pesticides on Honey Bees",slug:"impacts-of-pesticides-on-honey-bees",totalDownloads:3367,totalCrossrefCites:18,totalDimensionsCites:39,abstract:"This chapter focuses on the detrimental effects that pesticides have on managed honey bee colonies and their productivity. We examine first the routes of exposure of bees to agrochemicals used for crop protection and their application to crops, fate and contamination of water and plants around the fields. Most of the time, the exposure of bees to pesticides is through ingestion of residues found in the pollen and nectar of plants and in water. Honey bees are also exposed to pesticides used for the treatment of Varroa and other parasites. The basic concepts about the toxicity of the different kinds of pesticides are explained next. Various degrees of toxicity are found among agrochemicals, and emphasis is given to the classic tenet of toxicology, “the dose makes the poison,” and its modern version “the dose and the time of exposure makes the poison.” These two factors, dose and time, help us understand the severity of the impacts that pesticides may have on bees and their risk, which are analysed in the third section. Sublethal effects are also considered. The final section is devoted to some practical advice for avoiding adverse impacts of pesticides in beekeeping.",book:{id:"5163",slug:"beekeeping-and-bee-conservation-advances-in-research",title:"Beekeeping and Bee Conservation",fullTitle:"Beekeeping and Bee Conservation - Advances in Research"},signatures:"Francisco Sanchez-Bayo and Koichi Goka",authors:[{id:"74970",title:"Dr.",name:"Francisco",middleName:null,surname:"Sánchez-Bayo",slug:"francisco-sanchez-bayo",fullName:"Francisco Sánchez-Bayo"},{id:"192045",title:"Dr.",name:"Koichi",middleName:null,surname:"Goka",slug:"koichi-goka",fullName:"Koichi Goka"}]},{id:"59212",doi:"10.5772/intechopen.73864",title:"Insect Conservation for the Twenty-First Century",slug:"insect-conservation-for-the-twenty-first-century",totalDownloads:1941,totalCrossrefCites:7,totalDimensionsCites:14,abstract:"Insects have been immensely successful as an animal group. They dominate compositional diversity of all but the saltiest and coldest parts of the planet. Yet today insects are declining at a precipitous rate. This is of great concern in terms of impoverishment of Earth, and is also dire for us. Insects contribute to the maintenance of terrestrial and freshwater systems, their service delivery and their resilience. The meteoric impact of humans is challenging this dominance, yet so few people realize that the very fabric of life on which they depend is being unraveled at an alarming rate. Action is required, as are new perspectives, if we are to maintain insect diversity and services through the twenty-first century. Here, we review how we should view and act to have more effective insect diversity conservation based on six themes: (1) philosophy (establishing the ethical foundation), (2) research (the finding out), (3) policy (the framework for action), (4) psychology (understanding how to engage humans in insect conservation action), (5) practice (implementation of action), and (6) validation (establishing how well we are doing at conserving insects). We then overview some emergent challenges and solutions at both the species and landscape operational levels in agricultural, forestry, and urban environments.",book:{id:"6619",slug:"insect-science-diversity-conservation-and-nutrition",title:"Insect Science",fullTitle:"Insect Science-Diversity, Conservation and Nutrition"},signatures:"Michael J. Samways",authors:[{id:"233323",title:"Distinguished Prof.",name:"Michael",middleName:null,surname:"Samways",slug:"michael-samways",fullName:"Michael Samways"}]},{id:"79121",doi:"10.5772/intechopen.100416",title:"Botanical Insecticides Are a Non-Toxic Alternative to Conventional Pesticides in the Control of Insects and Pests",slug:"botanical-insecticides-are-a-non-toxic-alternative-to-conventional-pesticides-in-the-control-of-inse",totalDownloads:229,totalCrossrefCites:4,totalDimensionsCites:9,abstract:"Insect control for crops is one of the most critical global concerns. Pest management is an economic and ecological problem worldwide due to the human and environmental risks raised by most synthetic pesticide products. Botanical insecticides have resurfaced in popularity due to their low cost and low environmental impact, rather than their negative effects on human health. Botanical insecticides destroy only the insects they are meant to kill, leaving no residue on food or in the environment. Botanicals have long been used to combat pests. The compounds have many environmental advantages. However, as opposed to other bio-control pests and pathogens, their use was minimal during the twentieth century. In developing countries, botanical insecticides are well adapted for use in organic food production. Nonetheless, they may play a far bigger role in developed countries’ food production and post-harvest food protection. Consequently, the current chapter briefly addresses botanicals with active ingredients with insecticidal, antifeedant, or repellent properties.",book:{id:"10739",slug:null,title:"Global Decline of Insects",fullTitle:"Global Decline of Insects"},signatures:"Nazeer Ahmed, Mukhtar Alam, Muhammad Saeed, Hidayat Ullah, Toheed Iqbal, Khalid Awadh Al-Mutairi, Kiran Shahjeer, Rafi Ullah, Saeed Ahmed, Nibal Abd Aleem Hassan Ahmed, Hanem Fathy Khater and Muhammad Salman",authors:null},{id:"50307",doi:"10.5772/62654",title:"From Extraction to Meliponiculture: A Case Study of the Management of Stingless Bees in the West-Central Region of Mexico",slug:"from-extraction-to-meliponiculture-a-case-study-of-the-management-of-stingless-bees-in-the-west-cent",totalDownloads:2730,totalCrossrefCites:5,totalDimensionsCites:9,abstract:"Currently, stingless bees' populations are declining due to environmental degradation. In this context, the authors have developed a research project in the central-western region of Mexico with the goal to generate strategies for conservation and sustainable management of stingless bees. The chapter aims to present the process of this investigation and its main results in terms of a) local knowledge and management strategies of stingless bees, and b) the social process of technological appropriation of meliponiculture by beekeepers. We recognized specific knowledge on the biology and ecology of stingless bees that result in a system for identifying species and management strategies of wild populations of these bees based on the extraction of nests. The implementation of an innovative productive activity based on the principles of meliponiculture and current techniques has been well received by producers, which has led to the formation of the Meliponicultores Michoacanos del Balsas Association, which grows five species of stingless bees. The research suggests that conservation associated with the use of bees (integral meliponiculture) can be enhanced in the region. Faced with the loss of biodiversity and environmental crisis, it is essential to maintain and enhance local knowledge of stingless bees and management practices. This represents an alternative to develop management schemes that allow the raising and breeding of these bees, while its products are obtained.",book:{id:"5163",slug:"beekeeping-and-bee-conservation-advances-in-research",title:"Beekeeping and Bee Conservation",fullTitle:"Beekeeping and Bee Conservation - Advances in Research"},signatures:"Alejandro Reyes-González, Andrés Camou-Guerrero and Salvador\nGómez-Arreola",authors:[{id:"179951",title:"Dr.",name:"Andres",middleName:null,surname:"Camou-Guerrero",slug:"andres-camou-guerrero",fullName:"Andres Camou-Guerrero"},{id:"185413",title:"MSc.",name:"Alejandro",middleName:null,surname:"Reyes-González",slug:"alejandro-reyes-gonzalez",fullName:"Alejandro Reyes-González"},{id:"192049",title:"Dr.",name:"Salvador",middleName:null,surname:"Gómez-Arreola",slug:"salvador-gomez-arreola",fullName:"Salvador Gómez-Arreola"}]},{id:"50683",doi:"10.5772/63145",title:"Advances in Pharmacological Activities and Chemical Composition of Propolis Produced in Americas",slug:"advances-in-pharmacological-activities-and-chemical-composition-of-propolis-produced-in-americas",totalDownloads:2555,totalCrossrefCites:2,totalDimensionsCites:8,abstract:"Propolis is a resinous material produced by bees from the selective collection of plant exudates that are subsequently mixed with beeswax and salivary bee secretions. Propolis has been used in folk medicine, and certainly, several studies have validated its biological properties. The chemical composition and pharmacological activities of propolis collected through North (including Central America and Caribbean) and South America have been studied in the last years, and several papers have reported differences and similarities among the analysed geographical samples. Propolis has been classified according to its aspect and plant source; however, the ecological diversity present along the Americas provides a plethora of botanical resins. Herein, we summarize and discuss most of the studies performed at present on this profitable product for apiculture, attempting to compare the bioactivity, phytochemical diversity and botanical sources of honeybee propolis produced in Americas.",book:{id:"5163",slug:"beekeeping-and-bee-conservation-advances-in-research",title:"Beekeeping and Bee Conservation",fullTitle:"Beekeeping and Bee Conservation - Advances in Research"},signatures:"Efrain Alday, Moisés Navarro-Navarro, Adriana Garibay-Escobar,\nRamón Robles-Zepeda, Javier Hernandez and Carlos Velazquez",authors:[{id:"96966",title:"MSc.",name:"Moises",middleName:null,surname:"Navarro-Navarro",slug:"moises-navarro-navarro",fullName:"Moises Navarro-Navarro"},{id:"180409",title:"Dr.",name:"Carlos",middleName:null,surname:"Velazquez",slug:"carlos-velazquez",fullName:"Carlos Velazquez"},{id:"186351",title:"Dr.",name:"Ramón",middleName:null,surname:"Robles-Zepeda",slug:"ramon-robles-zepeda",fullName:"Ramón Robles-Zepeda"},{id:"186352",title:"MSc.",name:"Efrain",middleName:null,surname:"Alday",slug:"efrain-alday",fullName:"Efrain Alday"},{id:"186353",title:"Dr.",name:"Javier",middleName:null,surname:"Hernandez",slug:"javier-hernandez",fullName:"Javier Hernandez"},{id:"189161",title:"Dr.",name:"Adriana",middleName:null,surname:"Garibay-Escobar",slug:"adriana-garibay-escobar",fullName:"Adriana Garibay-Escobar"}]}],mostDownloadedChaptersLast30Days:[{id:"50170",title:"A Comprehensive Characterization of the Honeybees in Siberia (Russia)",slug:"a-comprehensive-characterization-of-the-honeybees-in-siberia-russia-",totalDownloads:2274,totalCrossrefCites:4,totalDimensionsCites:8,abstract:"A comprehensive study of some populations of honeybee (332 colonies) in Siberia (Tomsk region, Krasnoyarsk Krai (Yenisei population), Altai) using morphometric and molecular genetic methods was conducted. Infestation of bees (132 colonies) by Nosema has also been studied. Three variants of the COI-COII mtDNA locus were registered: PQQ, PQQQ (typical for Apis m. mellifera), and Q (specific for southern races). It was established that 64% of bee colonies from the Tomsk region and all colonies studied from the Krasnoyarsk and the Altai territories originate from Apis m. mellifera on the maternal line. According to the morphometric study, the majority of bee colonies of the Tomsk region are hybrids; in some colonies the mismatch of morphometric and mtDNA data was observed. Moreover, the majority of bee colonies infected by Nosema were hybrids. Yenisei population may be considered as a unique Apis m. mellifera population. Microsatellite analysis (loci А008, Ap049, AC117, AC216, Ap243, H110, A024, A113) showed the specific distribution of genotypes and alleles for some loci in the bees, which differ by geographical location. Loci A024 and Ap049 are of considerable interest for further study as candidate markers for differentiation of subspecies; locus A008 can be considered informative for determining of different ecotypes of Apis m. mellifera.",book:{id:"5163",slug:"beekeeping-and-bee-conservation-advances-in-research",title:"Beekeeping and Bee Conservation",fullTitle:"Beekeeping and Bee Conservation - Advances in Research"},signatures:"Nadezhda V. Ostroverkhova, Olga L. Konusova, Aksana N. Kucher\nand Igor V. Sharakhov",authors:[{id:"180112",title:"Ph.D.",name:"Nadezhda",middleName:null,surname:"Ostroverkhova",slug:"nadezhda-ostroverkhova",fullName:"Nadezhda Ostroverkhova"},{id:"180249",title:"Ms.",name:"Olga",middleName:null,surname:"Konusova",slug:"olga-konusova",fullName:"Olga Konusova"},{id:"180342",title:"Prof.",name:"Aksana",middleName:null,surname:"Kucher",slug:"aksana-kucher",fullName:"Aksana Kucher"},{id:"180343",title:"Prof.",name:"Igor",middleName:null,surname:"Sharakhov",slug:"igor-sharakhov",fullName:"Igor Sharakhov"}]},{id:"70501",title:"Southeast Asian Meliponiculture for Sustainable Livelihood",slug:"southeast-asian-meliponiculture-for-sustainable-livelihood",totalDownloads:1235,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Stingless bees (Apidae: Meliponini) are one of the most important pollinators of native plants and economic crops in tropical and subtropical parts of the world. They not only establish large perennial colonies with complex social organization but also have a diverse nesting biology. The economic utilization of a total of 60 stingless bee species in Asia has been reported. The current status of meliponiculture in Southeast Asia is mainly focused on pollination utilization and honey and propolis production. This chapter shows that small-scale beekeeping of stingless bees, which is suitable for the flowering pattern in the tropics, is one of the best potential alternative opportunities. The cost-effectiveness analysis based on production yield, investment cost, and profit-return rate is reviewed. Finally, a sustainable utilization of stingless bees is considered to be an enhancer of pollination services both in an agricultural crop and natural ecosystem.",book:{id:"8929",slug:"modern-beekeeping-bases-for-sustainable-production",title:"Modern Beekeeping",fullTitle:"Modern Beekeeping - Bases for Sustainable Production"},signatures:"Atsalek Rattanawannee and Orawan Duangphakdee",authors:[{id:"283087",title:"Ph.D.",name:"Atsalek",middleName:null,surname:"Rattanawannee",slug:"atsalek-rattanawannee",fullName:"Atsalek Rattanawannee"},{id:"306411",title:"Dr.",name:"Orawan",middleName:null,surname:"Duangphakdee",slug:"orawan-duangphakdee",fullName:"Orawan Duangphakdee"}]},{id:"50073",title:"Impacts of Pesticides on Honey Bees",slug:"impacts-of-pesticides-on-honey-bees",totalDownloads:3367,totalCrossrefCites:18,totalDimensionsCites:39,abstract:"This chapter focuses on the detrimental effects that pesticides have on managed honey bee colonies and their productivity. We examine first the routes of exposure of bees to agrochemicals used for crop protection and their application to crops, fate and contamination of water and plants around the fields. Most of the time, the exposure of bees to pesticides is through ingestion of residues found in the pollen and nectar of plants and in water. Honey bees are also exposed to pesticides used for the treatment of Varroa and other parasites. The basic concepts about the toxicity of the different kinds of pesticides are explained next. Various degrees of toxicity are found among agrochemicals, and emphasis is given to the classic tenet of toxicology, “the dose makes the poison,” and its modern version “the dose and the time of exposure makes the poison.” These two factors, dose and time, help us understand the severity of the impacts that pesticides may have on bees and their risk, which are analysed in the third section. Sublethal effects are also considered. The final section is devoted to some practical advice for avoiding adverse impacts of pesticides in beekeeping.",book:{id:"5163",slug:"beekeeping-and-bee-conservation-advances-in-research",title:"Beekeeping and Bee Conservation",fullTitle:"Beekeeping and Bee Conservation - Advances in Research"},signatures:"Francisco Sanchez-Bayo and Koichi Goka",authors:[{id:"74970",title:"Dr.",name:"Francisco",middleName:null,surname:"Sánchez-Bayo",slug:"francisco-sanchez-bayo",fullName:"Francisco Sánchez-Bayo"},{id:"192045",title:"Dr.",name:"Koichi",middleName:null,surname:"Goka",slug:"koichi-goka",fullName:"Koichi Goka"}]},{id:"74836",title:"Chironomidae: Biology, Ecology and Systematics",slug:"chironomidae-biology-ecology-and-systematics",totalDownloads:426,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The family of Chironomidae is a group of Diptera insects belonging to the suborder of Nematocera, commonly called “non-biting midges” in the adult stage and “bloodworms” in the larval stage. The Chironomidae are often the most abundant group of macroinvertebrates, in number of species and individuals, encountered in all aquatic environments of freshwater, brackish, terrestrial and even the sea. Likewise, Chironomidae occur in all the continents. The Chironomidae family is divided into 11 sub-families that have diffrent ecological statues. Despite the wealth of data on Chironomidae in the Holarctic region, other parts of the world are poorly studied and few guides to identifying Chironomidae have been produced. This chapter includes a theoretical synthesis on the Chironomidae, it deals with the Biology (life cycle and description of different stages), description of all subfamilies and the ecology of this important family of Diptera.",book:{id:"10423",slug:"the-wonders-of-diptera-characteristics-diversity-and-significance-for-the-world-s-ecosystems",title:"The Wonders of Diptera",fullTitle:"The Wonders of Diptera - Characteristics, Diversity, and Significance for the World's Ecosystems"},signatures:"Zerguine Karima",authors:[{id:"334825",title:"Dr.",name:"Karima",middleName:null,surname:"Zerguine",slug:"karima-zerguine",fullName:"Karima Zerguine"}]},{id:"75438",title:"Characteristics of Dipteran Insects",slug:"characteristics-of-dipteran-insects",totalDownloads:485,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Diptera means two wings (Di: two, pteron: wing). They have complete metamorphosis and they are holometabolous insects which means there are 4 stages (egg, larvae, pupae and adult). The name of larval stage is “maggot”. Some of the dipteran insects cause damage in agricultural production. Some are harmful for humans. Dipteran insects have two wings. Hind wings are reduced and they are called “halteres”. Function of halteres is balancing when the insects fly. Except mosquitoes, dipteran insects have sponging-sucking mouthparts. Important examples for dipteran insects are Olive fruit fly and Medfly which cause damages in agricultural production. OFF is the most destructive pest in olive growing areas and Mediterranean fruit fly cause damages in fruit production.",book:{id:"10423",slug:"the-wonders-of-diptera-characteristics-diversity-and-significance-for-the-world-s-ecosystems",title:"The Wonders of Diptera",fullTitle:"The Wonders of Diptera - Characteristics, Diversity, and Significance for the World's Ecosystems"},signatures:"Murat Helvacı",authors:[{id:"301984",title:"Ph.D.",name:"Murat",middleName:null,surname:"Helvaci",slug:"murat-helvaci",fullName:"Murat Helvaci"}]}],onlineFirstChaptersFilter:{topicId:"35",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"78491",title:"Insect Conservation and Management: A Need of the Hour",slug:"insect-conservation-and-management-a-need-of-the-hour",totalDownloads:26,totalDimensionsCites:0,doi:"10.5772/intechopen.100023",abstract:"Insects play a very vital role in divergent ecosystems and have gained great economic and medical importance as pollinators, pests, predators, parasitoids, decomposers and vectors. With the large-scale practice of synthetic pesticides, the diminishing rate of beneficial and pollinator insects is increasing rapidly. Environmental pollution, climate change, global warming, urbanization, industrialization and some natural calamities like wildfires add more fuel to the acceleration of insect decline all over the world. Alternative steps should be employed to replace the toxic pesticides and implementation of integrated pest management (IPM) should be put forward to reduce the overuse of synthetic pesticides and fertilizers, which have a great impact on beneficial insects as well as birds, aquatic organisms, and also on human health. The present study aims to create awareness among the researchers and general public by providing a brief review of insect importance, decline and conservation strategies.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Muzafar Riyaz, Rauf Ahmad Shah and Soosaimanickam Maria Packiam"},{id:"80971",title:"Agricultural Intensification Causes Decline in Insect Biodiversity",slug:"agricultural-intensification-causes-decline-in-insect-biodiversity",totalDownloads:47,totalDimensionsCites:0,doi:"10.5772/intechopen.101360",abstract:"The world’s population exceeded 7 billion in late 2011 and it is expected to reach 9.3 billion by 2050. Meanwhile, demand for food is predicted to increase between 50 and 100% by 2050. To meet the food demands of the increasing population, agricultural intensification practices including growing monocultures of high-yielding crop varieties and increased applications of fertilizers and pesticides have been used to increase productivity. These practices, however, impact negatively on biodiversity of existing flora and fauna, particularly causing huge declines in insect biodiversity. This chapter reviews present state of knowledge about agricultural intensification practices and global decline of insect biodiversity (i.e., pest and beneficial insect species) in intensive agricultural system and point out the likely drivers of these declines. It concludes the review by examining sustainable agricultural intensification practices that could be used to mitigate these biodiversity declines while maintaining productivity in intensive agricultural systems.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Mumuni Abudulai, Jerry Asalma Nboyine, Peter Quandahor, Ahmed Seidu and Fousséni Traore"},{id:"78872",title:"Diversity, Importance and Decline of Pollinating Insects in Present Era",slug:"diversity-importance-and-decline-of-pollinating-insects-in-present-era",totalDownloads:85,totalDimensionsCites:0,doi:"10.5772/intechopen.100316",abstract:"Pollination is a multi-million-year-old co-evolutionary process involving flowering plants and pollinators. It is one of the most important mechanisms in preservation and promotion of biodiversity as well as life on Earth. Pollinator diversity is essential for maintaining overall biological diversity in many habitats including agro-ecosystems. Pollinators are responsible for assisting reproduction in over 80% of the world’s flowering plants. In their absence, humans and wildlife would go hungry. Insects are the most efficient pollinators as they play a crucial part in pollination ecology. Pollinators and their habitats have ecological, economic, cultural and social benefits. Pollination efficiency is highly dependent on certain attributes and characteristics of pollinators such as vision, anatomy, food preferences, olfaction, behaviour and learning ability. With the rapid growth of human population, our demand for food has also risen. Our agricultural systems will need to produce more food in a sustainable manner in the future to cope with this. Pollinators play an important role in these ecosystems and will continue to do so in the future. Because pollinators are so important to agriculture, we need to learn more about which crops require specific pollinators and how to best maintain and promote both wild and controlled species. Their diversity needs protection because there are specific relationships between certain crops and pollinators. Pollinator communities are suffering as a result of man-made habitat disruptions, including severe biodiversity loss. This diversity must be protected by combining conservation measures with sustainable farming practices which could increase crop yields while protecting insect pollinator species.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Navkiran Kaur and Amritpal Singh Kaleka"},{id:"80012",title:"Impacts of Organic Farming on Insects Abundance and Diversity",slug:"impacts-of-organic-farming-on-insects-abundance-and-diversity",totalDownloads:107,totalDimensionsCites:0,doi:"10.5772/intechopen.102035",abstract:"Organic farming encourages maximum utilization of the natural biological processes to manage the farm in terms of soil fertilization and pest control, which implies using none or less synthetic fertilizers, pesticides, and plant and animal growth-promoting substances. All these practices increase arthropod diversity, particularly soil-dwelling insects. Intercropping, cover crops, and hedges, which are common practices in organic fields, provide alternative habitats for arthropod communities. The refugia also provide a good source of food for pollinators in terms of pollen grains and nectar. The interactions among the different plant and animal taxa (weeds, birds, mammals) that are found in the organic farming ecosystem have a great impact on insects’ abundance and diversity. This chapter summarizes the impacts of the organic farming system on the abundance and diversity of insects. The role of organic farming in mitigating the impact of agriculture intensification, urbanization, deforestation, and climate change on global insects’ decline and diversity loss is discussed.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Hamadttu Abdel Farag El-Shafie"},{id:"78945",title:"Botanical Insecticides and their Potential as Anti-Insect/Pests: Are they Successful against Insects and Pests?",slug:"botanical-insecticides-and-their-potential-as-anti-insect-pests-are-they-successful-against-insects-",totalDownloads:204,totalDimensionsCites:7,doi:"10.5772/intechopen.100418",abstract:"In low-income countries, subsistence and transitional farms frequently use botanical insecticides. The shortage or high cost of industrial pesticides also prompts their use. Botanical insecticides are also prescribed by agricultural and development programs and certain development organizations. However, since insecticidal proof of their effectiveness and protection might not be sufficient or usable, this may be called into question. While insecticidal botanicals have been extensively studied, there has yet to be a fusion that focuses especially on the domestic synthesis of biopesticides that work infield and storage effectively. In this chapter, we look at the effectiveness of botanicals (neem, garlic, and essential oil) that are used as insecticides. In addition, this chapter also focuses on research carried out on the use of these essential oils as insecticides. Processes that use variable amounts of ingredients and concentrations and ratios of active ingredients can have varying impacts on the efficacy of plant-based biological insecticides. Finally, using home-made insecticides would reduce the losses that occur during food production and enable us to use environment-friendly pest management methods.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Toheed Iqbal, Nazeer Ahmed, Kiran Shahjeer, Saeed Ahmed, Khalid Awadh Al-Mutairi, Hanem Fathy Khater and Reham Fathey Ali"},{id:"79060",title:"Description of a New Species of the Genus Anagrus (Hymenoptera: Chalcidoidea: Mymaridae): A Biocontrol Agent as an Alternative to Insecticide Use",slug:"description-of-a-new-species-of-the-genus-anagrus-hymenoptera-chalcidoidea-mymaridae-a-biocontrol-ag",totalDownloads:75,totalDimensionsCites:0,doi:"10.5772/intechopen.99957",abstract:"Although insects are economically important as they produce honey, silk, act as pollinators and also play an important role in functioning of an ecosystem, yet insect population is declining very fast. One of the possible causes of insects decline is excessive use of pesticides. Control of pest with synthetic chemicals or pesticides result in several issues and complications. These chemical pesticides or insecticides can also cause toxic effects on beneficial organisms like honeybees and butterflies which are important pollinators. So, biocontrol agents can be used as best alternative to control pest without harming beneficial organism and non-target insects or other organism as majority of biocontrol agents are host specific. Biological control agents including predators and parasotoids are natural enemies of insect pests. Present chapter deals with the description and illustration of one new species Anagrus (Anagrus) sololinearis sp.nov from India. This new species belongs to genus Anagrus (Hymenoptera: Chalcidoidea: Mymaridae). Genus Anagrus is considered as one of the important and most promising biocontrol agents in insects as it is an egg parasitoid.",book:{id:"10739",title:"Global Decline of Insects",coverURL:"https://cdn.intechopen.com/books/images_new/10739.jpg"},signatures:"Shireen Saleem and Shoeba Binte Anis"}],onlineFirstChaptersTotal:10},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"\r\n This topic aims to provide a comprehensive overview of the latest trends in Oral Health based on recent scientific evidence. Subjects will include an overview of oral diseases and infections, systemic diseases affecting the oral cavity, prevention, diagnosis, treatment, epidemiology, as well as current clinical recommendations for the management of oral, dental, and periodontal diseases.
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Her qualifications are: a specialist in Dental Imaging and Radiology, Master in Dentistry (Periodontics) from the University of São Paulo (FORP-USP, Ribeirão Preto, SP), and Doctor (Ph.D.) in Dentistry (Stomatology Clinic) from Hospital São Lucas of the Pontifical Catholic University of Rio Grande do Sul (HSL-PUCRS, Porto Alegre, RS). She held a postdoctoral internship at the Federal University from Jequitinhonha and Mucuri Valleys (UFVJM, Diamantina, MG). She is currently a member of the Brazilian Society for Dental Research (SBPqO) and the Brazilian Society of Stomatology and Pathology (SOBEP). 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