Seroprevalence of malaria in inhabitants of the urban zone of Antananarivo, Madagascar

BACKGROUND: Antananarivo, the capital of Madagascar, is located at an altitude of over 1,200 m. The environment at this altitude is not particularly favourable to malaria transmission, but malaria nonetheless remains a major public health problem. The aim of this study was to evaluate exposure to malaria in the urban population of Antananarivo, by measuring the specific seroprevalence of Plasmodium falciparum. METHODS: Serological studies specific for P. falciparum were carried out with an indirect fluorescent antibody test (IFAT). In a representative population of Antananarivo, 1,059 healthy volunteers were interviewed and serum samples were taken. RESULTS: The seroprevalence of IgG+IgA+IgM was 56.1% and that of IgM was 5.9%. The major risk factor associated with a positive IgG+IgA+IgM IFAT was travel outside Antananarivo, whether in the central highlands or on the coast. The abundance of rice fields in certain urban districts was not associated with a higher seroprevalence. CONCLUSION: Malaria transmission levels are low in Antananarivo, but seroprevalence is high. Humans come into contact with the parasite primarily when travelling outside the city. Further studies are required to identify indigenous risk factors and intra-city variations more clearly

Access to administrative documents and to public sector information in Italy

Law No. 241 of 1990 on administrative procedure (Italian APA) established general rules on the right of access to administrative documents for the first time in the Italian legal system, which partly reproduced rules defined in sectorial legislations. From such very restrictive regime of access to administrative documents\u2014lately accompanied by a rather demagogical obligation imposed on public administrations to disclose a set of information in the context of the so-called open data policies\u2014Italy has recently moved forth to public access to data and documents held by public administrations

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

BACKGROUND: During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. METHODS: The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. RESULTS: The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). CONCLUSION: Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities

Anopheles larval abundance and diversity in three rice agro-village complexes Mwea irrigation scheme, central Kenya

<p>Abstract</p> <p>Background</p> <p>The diversity and abundance of <it>Anopheles </it>larvae has significant influence on the resulting adult mosquito population and hence the dynamics of malaria transmission. Studies were conducted to examine larval habitat dynamics and ecological factors affecting survivorship of aquatic stages of malaria vectors in three agro-ecological settings in Mwea, Kenya.</p> <p>Methods</p> <p>Three villages were selected based on rice husbandry and water management practices. Aquatic habitats in the 3 villages representing planned rice cultivation (Mbui Njeru), unplanned rice cultivation (Kiamachiri) and non-irrigated (Murinduko) agro-ecosystems were sampled every 2 weeks to generate stage-specific estimates of mosquito larval densities, relative abundance and diversity. Records of distance to the nearest homestead, vegetation coverage, surface debris, turbidity, habitat stability, habitat type, rice growth stage, number of rice tillers and percent <it>Azolla </it>cover were taken for each habitat.</p> <p>Results</p> <p>Captures of early, late instars and pupae accounted for 78.2%, 10.9% and 10.8% of the total <it>Anopheles </it>immatures sampled (n = 29,252), respectively. There were significant differences in larval abundance between 3 agro-ecosystems. The village with 'planned' rice cultivation had relatively lower <it>Anopheles </it>larval densities compared to the villages where 'unplanned' or non-irrigated. Similarly, species composition and richness was higher in the two villages with either 'unplanned' or limited rice cultivation, an indication of the importance of land use patterns on diversity of larval habitat types. Rice fields and associated canals were the most productive habitat types while water pools and puddles were important for short periods during the rainy season. Multiple logistic regression analysis showed that presence of other invertebrates, percentage <it>Azolla </it>cover, distance to nearest homestead, depth and water turbidity were the best predictors for <it>Anopheles </it>mosquito larval abundance.</p> <p>Conclusion</p> <p>These results suggest that agricultural practices have significant influence on mosquito species diversity and abundance and that certain habitat characteristics favor production of malaria vectors. These factors should be considered when implementing larval control strategies which should be targeted based on habitat productivity and water management.</p

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

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