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Risk Factors for Household Vector Abundance Using Indoor CDC Light Traps in a High Malaria Transmission Area of Northern Zambia
Marisa A. Hast
Marisa A. Hast
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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Jennifer C. Stevenson
Jennifer C. Stevenson
Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Macha Research Trust, Choma District, Zambia;
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Macha Research Trust, Choma District, Zambia;
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Mbanga Muleba
Mbanga Muleba
The Tropical Diseases Research Centre, Ndola, Zambia
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Mike Chaponda
Mike Chaponda
The Tropical Diseases Research Centre, Ndola, Zambia
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Jean-Bertin Kabuya
Jean-Bertin Kabuya
The Tropical Diseases Research Centre, Ndola, Zambia
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Modest Mulenga
Modest Mulenga
The Tropical Diseases Research Centre, Ndola, Zambia
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Justin Lessler
Justin Lessler
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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Timothy Shields
Timothy Shields
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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William J. Moss
William J. Moss
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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Douglas E. Norris
Douglas E. Norris
Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
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for the Southern and Central Africa International Centers of Excellence in Malaria Research
for the Southern and Central Africa International Centers of Excellence in Malaria Research
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Macha Research Trust, Choma District, Zambia;
The Tropical Diseases Research Centre, Ndola, Zambia
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Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;
Macha Research Trust, Choma District, Zambia;
The Tropical Diseases Research Centre, Ndola, Zambia
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Malaria transmission is dependent on the density and distribution of mosquito vectors, but drivers of vector abundance have not been adequately studied across a range of transmission settings. To inform intervention strategies for high-burden areas, further investigation is needed to identify predictors of vector abundance. Active household (HH) surveillance was conducted in Nchelenge district, Luapula Province, northern Zambia, a high-transmission setting with limited impact of malaria control. Between April 2012 and July 2017, mosquitoes were collected indoors during HH visits using CDC light traps. Demographic, environmental, and climatological correlates of vector abundance were identified using log-binomial regression models with robust standard errors. The primary malaria vectors in this setting were Anopheles funestus sensu stricto (s.s.) and Anopheles gambiae s.s. Anopheles funestus predominated in both seasons, with a peak in the dry season. Anopheles gambiae peaked at lower numbers in the rainy season. Environmental, climatic, and demographic factors were correlated with HH vector abundance. Higher vector counts were found in rural areas with low population density and among HHs close to roads and small streams. Vector counts were lower with increasing elevation and slope. Anopheles funestus was negatively associated with rainfall at lags of 2–6 weeks, and An. gambiae was positively associated with rainfall at lags of 3–10 weeks. Both vectors had varying relationships with temperature. These results suggest that malaria vector control in Nchelenge district should occur throughout the year, with an increased focus on dry-season transmission and rural areas.
Author Notes
Financial support: This work was supported by funds from the National Institutes of Health awarded to the Southern and Central Africa International Centers of Excellence in Malaria Research (ICEMR) 3U19AI089680, the Bloomberg Philanthropies, and the Johns Hopkins Malaria Research Institute (JHMRI).
Disclosure: W. J. M. reports grants from National Institute of Allergy and Infectious Diseases during the conduct of the study. J. L. reports grants from NIH during the conduct of the study. M. M. reports grants from Johns Hopkins Bloomberg School of Public Health through NIH funding to ICEMRs during the conduct of the study.
Authors’ addresses: Marisa A. Hast, Justin Lessler, Timothy Shields, William J. Moss, and Douglas E. Norris, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, E-mails: mhast2@jhu.edu, justin@jhu.edu, tshields@jhu.edu, wmoss1@jhu.edu, and douglas.norris@jhu.edu. Jennifer C. Stevenson, Macha Research Trust, Choma District, Zambia, E-mail: jennyc.stevenson@macharesearch.org. Mbanga Muleba, Mike Chaponda, Jean-Bertin Kabuya, and Modest Mulenga, Tropical Diseases Research Centre, Ndola, Zambia, E-mails: mulebam@tdrc.org.zm, chapondam@tdrc.org.zm, kabuyaj@tdrc.org.zam, and mulengam@tdrc.org.zm.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
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1.
World Health Organization, 2017. World Malaria Report 2017. Geneva, Switzerland: WHO.
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2.
World Health Organization, 2015. Global Technical Strategy for Malaria 2016–2030. Geneva, Switzerland: WHO.
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11.
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12.
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13.
Kirby MJ, Green C, Milligan PM, Sismanidis C, Jasseh M, Conway DJ, Lindsay SW, 2008. Risk factors for house-entry by malaria vectors in a rural town and satellite villages in the Gambia. Malar J 7: 2.
-
14.
Kaindoa EW, Mkandawile G, Ligamba G, Kelly-Hope LA, Okumu FO, 2016. Correlations between household occupancy and malaria vector biting risk in rural Tanzanian villages: implications for high-resolution spatial targeting of control interventions. Malar J 15: 199.
-
15.
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-
16.
Walker M, Winskill P, Basáñez MG, Mwangangi JM, Mbogo C, Beier JC, Midega JT, 2013. Temporal and micro-spatial heterogeneity in the distribution of Anopheles vectors of malaria along the Kenyan coast. Parasit Vectors 6: 311.
-
17.
Kabbale FG, Akol AM, Kaddu JB, Onapa AW, 2013. Biting patterns and seasonality of Anopheles gambiae sensu lato and Anopheles funestus mosquitoes in Kamuli District, Uganda. Parasit Vectors 6: 340.
-
18.
Koenraadt CJ, Githeko AK, Takken W, 2004. The effects of rainfall and evapotranspiration on the temporal dynamics of Anopheles gambiae s.s. and Anopheles arabiensis in a Kenyan village. Acta Trop 90: 141–153.
-
19.
Lindsay SW, Parson L, Thomas CJ, 1998. Mapping the ranges and relative abundance of the two principal African malaria vectors, Anopheles gambiae sensu stricto and An. arabiensis, using climate data. Proc Biol Sci 265: 847–854.
-
20.
Moffett A, Shackelford N, Sarkar S, 2007. Malaria in Africa: vector species’ niche models and relative risk maps. PLoS One 2: e824.
-
21.
Mbogo CM et al. 2003. Spatial and temporal heterogeneity of Anopheles mosquitoes and Plasmodium falciparum transmission along the Kenyan coast. Am J Trop Med Hyg 68: 734–742.
-
22.
Masaninga F et al. 2013. Review of the malaria epidemiology and trends in Zambia. Asian Pac J Trop Biomed 3: 89–94.
-
23.
Mharakurwa S, Thuma PE, Norris DE, Mulenga M, Chalwe V, Chipeta J, Munyati S, Mutambu S, Mason PR; Southern Africa ICEMR Team, 2012. Malaria epidemiology and control in Southern Africa. Acta Trop 121: 202–206.
-
24.
Mukonka VM et al. 2014. High burden of malaria following scale-up of control interventions in Nchelenge district, Luapula Province, Zambia. Malar J 13: 153.
-
25.
Kamuliwo M et al. 2013. The changing burden of malaria and association with vector control interventions in Zambia using district-level surveillance data, 2006–2011. Malar J 12: 437.
-
26.
Chanda E et al. 2011. Insecticide resistance and the future of malaria control in Zambia. PLoS One 6: e24336.
-
27.
Das S, Muleba M, Stevenson JC, Norris DE; Southern Africa International Centers of Excellence for Malaria Research Team, 2016. Habitat partitioning of malaria vectors in Nchelenge district, Zambia. Am J Trop Med Hyg 94: 1234–1244.
-
28.
Stevenson JC et al. Southern Africa International Centers of Excellence in Malaria Research, 2016. Spatio-temporal heterogeneity of malaria vectors in northern Zambia: implications for vector control. Parasit Vectors 9: 510.
-
29.
Kent RJ, Thuma PE, Mharakurwa S, Norris DE, 2007. Seasonality, blood feeding behavior, and transmission of Plasmodium falciparum by Anopheles arabiensis after an extended drought in southern Zambia. Am J Trop Med Hyg 76: 267–274.
-
30.
Lobo NF et al. 2015. Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools. Sci Rep 5: 17952.
-
31.
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-
32.
Zahar AR, 1985. Vector Bionomics in the Epidemiology and Control of Malaria. Geneva, Switzerland: WHO.
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Moss WJ, Norris DE, Mharakurwa S, Scott A, Mulenga M, Mason PR, Chipeta J, Thuma PE; Southern Africa ICEMR Team, 2012. Challenges and prospects for malaria elimination in the Southern Africa region. Acta Trop 121: 207–211.
-
34.
Olayemi IK, Ande AT, 2009. Life table analysis of Anopheles gambiae (Diptera: Culicidae) in relation to malaria transmission. J Vector Borne Dis 46: 295–298.
-
35.
Okoye PN, Brooke BD, Hunt RH, Coetzee M, 2007. Relative developmental and reproductive fitness associated with pyrethroid resistance in the major southern African malaria vector, Anopheles funestus. Bull Entomol Res 97: 599–605.
-
36.
Moss WJ et al. 2015. Malaria epidemiology and control within the International Centers of Excellence for Malaria Research. Am J Trop Med Hyg 93: 5–15.
-
37.
Zambia National Malaria Control Programme, 2017. Lusaka, Zambia. Personal communication.
-
38.
USAID, President’s Malaria Initiative, 2017. Zambia Malaria Operational Plan FY 2018. Lusaka, Zambia: USAID.
-
39.
Pinchoff J, Chaponda M, Shields TM, Sichivula J, Muleba M, Mulenga M, Kobayashi T, Curriero FC, Moss WJ; Southern Africa International Centers of Excellence for Malaria Research, 2016. Individual and household level risk factors associated with malaria in Nchelenge district, a region with perennial transmission: a serial cross-sectional study from 2012 to 2015. PLoS One 11: e0156717.
-
40.
Yates F, Grundy PM, 1953. Selection without replacement from within strata with probability proportional to size. J R Stat Soc Ser B 15: 253–261.
-
41.
Gillies M, de Meillon B, 1968. The Anophelinae of Africa South of the Sahara, 2nd edition. Johannesburg, South Africa: South African Institute of Medical Research.
-
42.
Gillies M, Coetzee M, 1987. A Supplement to the Anophelinae of Africa South of the Sahara: Afrotropical Region. Johannesburg, South Africa: South African Institute for Medical Research.
-
43.
Scott JA, Brogdon WG, Collins FH, 1993. Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction. Am J Trop Med Hyg 49: 520–529.
-
44.
Koekemoer LL, Kamau L, Hunt RH, Coetzee M, 2002. A cocktail polymerase chain reaction assay to identify members of the Anopheles funestus (Diptera: Culicidae) group. Am J Trop Med Hyg 66: 804–811.
-
45.
Sheffield J et al. 2014. A drought monitoring and forecasting system for sub-Sahara African water resources and food security. Bull Am Meteorol Soc 95: 861–882.
-
46.
Princeton University, 2014. African Flood and Drought Monitor. Available at: http://stream.princeton.edu/AWCM/WEBPAGE/interface.php. Accessed September 1, 2017.
-
47.
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG, 2009. Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42: 377–381.
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