4 research outputs found
Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.
BACKGROUND: In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. METHODS: This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. RESULTS: From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. CONCLUSION: Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal
Identifying malaria hotspots in Keur Soce health and demographic surveillance site in context of low transmission
Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site
Community case management in malaria: review and perspectives after four years of operational experience in Saraya district, south-east Senegal.
BACKGROUND: Despite recent advances in malaria diagnosis and treatment, many isolated communities in rural settings continue to lack access to these life-saving tools. Community-case management of malaria (CCMm), consisting of lay health workers (LHWs) using malaria rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACT) in their villages, can address this disparity. METHODS: This study examined routine reporting data from a CCMm programme between 2008 and 2011 in Saraya, a rural district in Senegal, and assessed its impact on timely access to rapid diagnostic tests and ACT. RESULTS: There was a seven-fold increase in the number of LHWs providing care and in the number of patients seen. LHW engagement in the CCM programme varied seasonally, 24,3% of all patients prescribed an ACT had a negative RDT or were never administered an RDT, and less than half of patients with absolute indications for referral (severe symptoms, age under two months and pregnancy) were referred. There were few stock-outs. DISCUSSION: This CCMm programme successfully increased the number of patients with access to RDT and ACT, but further investigation is required to identify the cause for over-prescription, and low rates of referrals for patients with absolute indications. In contrast, previous widespread stock-outs in Saraya's CCMm programme have now been resolved. CONCLUSION: This study demonstrates the potential for CCMm programmes to substantially increase access to life-saving malarial diagnostics and treatment, but also highlights important challenges in ensuring quality