Abstract
BackgroundMalaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions.MethodsSpatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit.ResultsMalaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages.ConclusionThe study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.
Highlights
Malaria attacks are not evenly distributed in space and time
The most likely spatial clusters were detected in highaltitude kebeles: Janbelew, Tenseye, Doka, Defiya, Doromamaye, Wekentown, Talakmesk, Abetera, and Weken Zurya (LLR = 16.23, p < 0.001)
The secondary clusters were found at kebeles: Carbita, Dara, and Benker (LLR = 4.58, p < 0.04) and accounted for 147 (22.8%) of malaria cases (Figure 3)
Summary
Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Malaria transmission varies in space and time [1,2] It is a multifactorial disease and the aetiological agent has a complex life cycle requiring an insect vector, and the attribution of trends to specific factors remains difficult because of multiple drivers, including micro-ecology, utilization of interventions, demographic and population movement [3], drug resistance, land-use change, and access to health facilities [4,5]. Understanding heterogeneity should focus [8] on individuals who contribute disproportionately to malaria transmission and other driving factors. Such targeted interventions are supremely important tools in malaria elimination efforts [15]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
