Daniel J Bridges1,2, Sandra Chishimba3,4, Mulenga Mwenda3,4, Anna M Winters4,5, Erik Slawsky6, Brenda Mambwe3, Conceptor Mulube3, Kelly M Searle7, Aves Hakalima8, Roy Mwenechanya4,9, David A Larsen4,6. 1. PATH MACEPA, National Malaria Elimination Centre, Gt East Rd, Lusaka, Zambia. dbridges@path.org. 2. Akros, 45A Roan Road, Lusaka, Zambia. dbridges@path.org. 3. PATH MACEPA, National Malaria Elimination Centre, Gt East Rd, Lusaka, Zambia. 4. Akros, 45A Roan Road, Lusaka, Zambia. 5. School of Public and Community Health Sciences, University of Montana, Missoula, MT, USA. 6. Department of Public Health, Syracuse University, Syracuse, NY, USA. 7. School of Public Health, University of Minnesota, Minneapolis, MN, USA. 8. Lusaka District Health Management Team, Ministry of Health, Lusaka, Zambia. 9. Department of Biomedical Sciences, School of Veterinary Medicine, University of Zambia, Lusaka, Zambia.
Abstract
BACKGROUND: Zambia has set itself the ambitious target of eliminating malaria by 2021. To continue tracking transmission to zero, new interventions, tools and approaches are required. METHODS: Urban reactive case detection (RCD) was performed in Lusaka city from 2011 to 2015 to better understand the location and drivers of malaria transmission. Briefly, index cases were followed to their home and all consenting individuals living in the index house and nine proximal houses were tested with a malaria rapid diagnostic test and treated if positive. A brief survey was performed and for certain responses, a dried blood spot sample collected for genetic analysis. Aggregate health facility data, individual RCD response data and genetic results were analysed spatially and against environmental correlates. RESULTS: Total number of malaria cases remained relatively constant, while the average age of incident cases and the proportion of incident cases reporting recent travel both increased. The estimated R0 in Lusaka was < 1 throughout the study period. RCD responses performed within 250 m of uninhabited/vacant land were associated with a higher probability of identifying additional infections. CONCLUSIONS: Evidence suggests that the majority of malaria infections are imported from outside Lusaka. However there remains some level of local transmission occurring on the periphery of urban settlements, namely in the wet season. Unfortunately, due to the higher-than-expected complexity of infections and the small number of samples tested, genetic analysis was unable to identify any meaningful trends in the data.
BACKGROUND: Zambia has set itself the ambitious target of eliminating malaria by 2021. To continue tracking transmission to zero, new interventions, tools and approaches are required. METHODS: Urban reactive case detection (RCD) was performed in Lusaka city from 2011 to 2015 to better understand the location and drivers of malaria transmission. Briefly, index cases were followed to their home and all consenting individuals living in the index house and nine proximal houses were tested with a malaria rapid diagnostic test and treated if positive. A brief survey was performed and for certain responses, a dried blood spot sample collected for genetic analysis. Aggregate health facility data, individual RCD response data and genetic results were analysed spatially and against environmental correlates. RESULTS: Total number of malaria cases remained relatively constant, while the average age of incident cases and the proportion of incident cases reporting recent travel both increased. The estimated R0 in Lusaka was < 1 throughout the study period. RCD responses performed within 250 m of uninhabited/vacant land were associated with a higher probability of identifying additional infections. CONCLUSIONS: Evidence suggests that the majority of malaria infections are imported from outside Lusaka. However there remains some level of local transmission occurring on the periphery of urban settlements, namely in the wet season. Unfortunately, due to the higher-than-expected complexity of infections and the small number of samples tested, genetic analysis was unable to identify any meaningful trends in the data.
Authors: João L Ferrão; Dominique Earland; Anísio Novela; Roberto Mendes; Marcos F Ballat; Alberto Tungaza; Kelly M Searle Journal: Int J Environ Res Public Health Date: 2021-03-05 Impact factor: 3.390