Spatially aggregated clusters and scattered smaller loci of elevated malaria vector density and human infection prevalence in urban Dar es Salaam, Tanzania
| Autor: | Victoria M. Mwakalinga, Yeromin P. Mlacha, Zawadi D. Mageni, Benn Sartorius, Nicodem J. Govella, Gerry F. Killeen, Stefan Dongus, Maureen Coetzee, John M. Paliga, Alex J. Limwagu, Daniel Msellemu |
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| Rok vydání: | 2015 |
| Předmět: |
medicine.medical_specialty
Anopheles gambiae 030231 tropical medicine Plasmodium falciparum wc_765 Tanzania law.invention 03 medical and health sciences 0302 clinical medicine Mosquito law parasitic diseases Anopheles medicine Prevalence Animals Cluster Analysis Humans 030212 general & internal medicine Malaria Falciparum biology Research wa_240 biology.organism_classification medicine.disease Spatial clustering Virology Confidence interval Vector control 3. Good health Insect Vectors Malaria Transmission (mechanics) Infectious Diseases Cross-Sectional Studies qx_650 Mapping wb_700 Vector (epidemiology) Tropical medicine Parasitology Hotspots Cartography |
| Zdroj: | Malaria Journal |
| ISSN: | 1475-2875 |
| Popis: | Background: Malaria transmission, primarily mediated by Anopheles gambiae, persists in Dar es Salaam (DSM) despite high coverage with bed nets, mosquito-proofed housing and larviciding. New or improved vector control strategies are required to eliminate malaria from DSM, but these will only succeed if they are delivered to the minority of locations where residual transmission actually persists. Hotspots of spatially clustered locations with elevated malaria infection prevalence or vector densities were, therefore, mapped across the city in an attempt to provide a basis for targeting supplementary interventions.Methods: Two phases of a city-wide population-weighted random sample of cross-sectional household surveys of malaria infections were complemented by two matching phases of geographically overlapping, high-resolution, longitudinal vector density surveys; spanning 2010–2013. Spatial autocorrelations were explored using Moran’s I and hotspots were detected using flexible spatial scan statistics.Results: Seven hotspots of spatially clustered elevated vector density and eight of malaria infection prevalence were detected over both phases. Only a third of vectors were collected in hotspots in phase 1 (30 %) and phase 2 (33 %). Malaria prevalence hotspots accounted for only half of malaria infections detected in phase 1 (55 %) and phase 2 (47 %). Three quarters (76 % in phase 1 and 74 % in phase 2) of survey locations with detectable vector populations were outside of hotspots. Similarly, more than half of locations with higher infection prevalence (>10 %) occurred outside of hotspots (51 % in phase 1 and 54 % in phase 2). Vector proliferation hazard (exposure to An. gambiae) and malaria infection risk were only very loosely associated with each other (Odds ratio (OR) [95 % Confidence Interval (CI)] = 1.56 [0.89, 1.78], P = 0.52)).Conclusion: Many small, scattered loci of local malaria transmission were haphazardly scattered across the city, so interventions targeting only currently identifiable spatially aggregated hotspots will have limited impact. Routine, spatially comprehensive, longitudinal entomological and parasitological surveillance systems, with sufficient sensitivity and spatial resolution to detect these scattered loci, are required to eliminate transmission from this typical African city. Intervention packages targeted to both loci and hotspots of transmission will need to suppress local vector proliferation, treat infected residents and provide vulnerable residents with supplementary protective measures against exposure. |
| Databáze: | OpenAIRE |
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