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

Mapping Urban Malaria and Diarrhea Mortality in Accra, Ghana: Evidence of Vulnerabilities and Implications for Urban Health Policy

Fobil JN, Levers C, Lakes T, Loag W, Krämer A, May J. Mapping Urban Malaria and Diarrhea Mortality in Accra, Ghana: Evidence of Vulnerabilities and Implications for Urban Health Policy. Journal Of Urban Health. 2012;89(6):977-991.Historic increase in urban population numbers in the face of shrinking urban economies and declining social services has meant that a large proportion of the urban population lives in precarious urban conditions, which provide the grounds for high urban health risks in low income countries. This study aims to identify, investigate, and contrast the spatial patterns of vulnerability and risk of two major causes of mortality, viz malaria and diarrhea mortalities, in order to optimize resource allocation for effective urban environmental management and improvement in urban health. A spatial cluster analysis of the observed urban malaria and diarrhea mortalities for the whole city of Accra was conducted. We obtained routinely reported mortality data for the period 1998-2002 from the Ghana Vital Registration System (VRS), computed the fraction of deaths due to malaria and diarrhea at the census cluster level, and analyzed and visualized the data with Geographic Information System (GIS, ArcMap 9.3.1). Regions of identified hotspots, cold spots, and excess mortalities were observed to be associated with some socioeconomic and neighborhood urban environmental conditions, suggesting uneven distribution of risk factors for both urban malaria and diarrhea in areas of rapid urban transformation. Case-control and/or longitudinal studies seeking to understand the individual level factors which mediate socioenvironmental conditions in explaining the observed excess urban mortalities and to establish the full range of risk factors might benefit from initial vulnerability mapping and excess risk analysis using geostatistical approaches. This is key to evidence-based urban health policy reforms in rapidly urbanizing areas in low income economies