10 research outputs found
Host choice and multiple blood feeding behaviour of malaria vectors and other anophelines in Mwea rice scheme, Kenya
<p>Abstract</p> <p>Background</p> <p>Studies were conducted between April 2004 and February 2006 to determine the blood-feeding pattern of <it>Anopheles </it>mosquitoes in Mwea Kenya.</p> <p>Methods</p> <p>Samples were collected indoors by pyrethrum spay catch and outdoors by Centers for Disease Control light traps and processed for blood meal analysis by an Enzyme-linked Immunosorbent Assay.</p> <p>Results</p> <p>A total of 3,333 blood-fed <it>Anopheles </it>mosquitoes representing four <it>Anopheles </it>species were collected and 2,796 of the samples were assayed, with <it>Anopheles arabiensis </it>comprising 76.2% (n = 2,542) followed in decreasing order by <it>Anopheles coustani </it>8.9% (n = 297), <it>Anopheles pharoensis </it>8.2% (n = 272) and <it>Anopheles funestus </it>6.7% (n = 222). All mosquito species had a high preference for bovine (range 56.3–71.4%) over human (range 1.1–23.9%) or goat (0.1–2.2%) blood meals. Some individuals from all the four species were found to contain mixed blood meals. The bovine blood index (BBI) for <it>An. arabiensis </it>was significantly higher for populations collected indoors (71.8%), than populations collected outdoors (41.3%), but the human blood index (HBI) did not differ significantly between the two populations. In contrast, BBI for indoor collected <it>An. funestus </it>(51.4%) was significantly lower than for outdoor collected populations (78.0%) and the HBI was significantly higher indoors (28.7%) than outdoors (2.4%). Anthropophily of <it>An. funestus </it>was lowest within the rice scheme, moderate in unplanned rice agro-ecosystem, and highest within the non-irrigated agro-ecosystem. Anthropophily of <it>An. arabiensis </it>was significantly higher in the non-irrigated agro-ecosystem than in the other agro-ecosystems.</p> <p>Conclusion</p> <p>These findings suggest that rice cultivation has an effect on host choice by <it>Anopheles </it>mosquitoes. The study further indicate that zooprophylaxis may be a potential strategy for malaria control, but there is need to assess how domestic animals may influence arboviruses epidemiology before adapting the strategy.</p
Prevalence of pfmdr1, pfcrt, pfdhfr and pfdhps mutations associated with drug resistance, in Luanda, Angola
<p>Abstract</p> <p>Background</p> <p>Malaria is the infectious disease causing the highest morbidity and mortality in Angola and due to widespread chloroquine (CQ) resistance, the country has recently changed its first-line treatment recommendations for uncomplicated malaria, from CQ to artemisinin combination therapies (ACT) in adults, and sulphadoxine/pyrimethamine (S/P) in pregnant women. Loss of SP sensitivity is, however, progressing rapidly in Africa and, in this study, were investigated a number of molecular markers associated to CQ and S/P.</p> <p>Methods</p> <p>Blood samples were collected from 245 children with uncomplicated malaria, admitted at the Pediatric Hospital Dr. David Bernardino (HPDB), Angola, and the occurrence of mutations in <it>Plasmodium falciparum </it>was investigated in the <it>pfmdr1 </it>(N86Y) and <it>pfcrt </it>(K76T) genes, associated with CQ resistance, as well as in <it>pfdhfr </it>(C59R) and <it>pfdhps </it>(K540E), conferring SP resistance.</p> <p>Results</p> <p>The frequencies of <it>pfmdr1 </it>mutations in codon 86 were 28.6% N, 61.3% Y and 10.1% mixed infections (NY). The frequency of <it>pfcrt </it>mutations in codon 76 were 93.9% K, 5.7% T and 0.4% mixed infections (KT). For <it>pfdhfr </it>the results were in codon 59, 60.6% C, 20.6% R and 18.8% mixed infections (CR). Concerning <it>pfdhps</it>, 6.3% of the isolates were bearers of the mutation 540E and 5.4% mixed infections (K540E).</p> <p>Conclusion</p> <p>The results of this epidemiologic study showed high presence of CQ resistance markers while for SP a much lower prevalence was detected for the markers under study.</p
Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps
A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km). Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes). For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis) these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The “additive” model assumes no interaction; the “minimax” model assumes maximum relative risk due to any vector in a cell; and the “competitive exclusion” model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease
Asymptomatic Plasmodium falciparum infections may not be shortened by acquired immunity
The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis
<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p
A reduction in malaria transmission intensity in Northern Ghana after 7Â years of indoor residual spraying
Geo-spatial factors associated with infection risk among young children in rural Ghana: a secondary spatial analysis
The state of enrollment on the National Health Insurance Scheme in rural Ghana after eight years of implementation
Tropical infectious diseases: Urbanization, malaria transmission and disease burden in Africa
Many attempts have been made to quantify Africa’s malaria burden but none has addressed how urbanization will affect disease transmission and outcome, and therefore mortality and morbidity estimates. In 2003, 39% of Africa’s 850 million people lived in urban settings; by 2030, 54% of Africans are expected to do so. We present the results of a series of entomological, parasitological and behavioural metaanalyses of studies that have investigated the effect of urbanization on malaria in Africa. We describe the effect of urbanization on both the impact of malaria transmission and the concomitant improvements in access to preventative and curative measures. Using these data, we have recalculated estimates of populations at risk of malaria and the resulting mortality. We find there were 1,068,505 malaria deaths in Africa in 2000 — a modest 6.7% reduction over previous iterations. The public-health implications of these findings and revised estimates are discussed