ORCID Profile
0000-0003-1029-8675
Current Organisations
Ghana Health Service
,
The Chinese University of Hong Kong
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Publisher: Research Square Platform LLC
Date: 12-01-2021
DOI: 10.21203/RS.3.RS-143819/V1
Abstract: Background: Efforts towards malaria control in Ghana have had positive impacts. However, these efforts need to be locally tailored to further accelerate progress. The aim of this study was to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation of malaria burden. Methodology: Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System from 2015 to 2019. Malaria cases were decomposed using the seasonal-trend decomposition, based on locally weighted regression to analyze the seasonality. A Poisson regression model with a conditional autoregressive prior structure was used to quantify associations between climatic variables and malaria risk, and spatial dependence. Posterior parameters were estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs s ling. Results: A total of 1,105,370 malaria cases was recorded in the region from 2015–2019. The overall malaria incidence rate for the region was approximately 1 per 1,000,000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern during the study period. Malaria incidence was found to increase by 0.1% (95% credible interval [CrI]: 0.02–0.16%) for a 1°C rise in monthly mean maximum temperature lagged at 6 months and 0.2% (95% CrI: 0.5–0.3%) for 1°C rise in monthly mean minimum temperature without lag. No spatial dependency was observed after accounting for climatic variables. Only five districts located in the south-central part of the region had a malaria incidence rate that was lower than the regional average at 95% probability level. Conclusion: The distribution of malaria cases was heterogeneous, seasonal and significantly associated with climatic variables. Targeted malaria control and prevention in high-risk districts at the appropriate time points could result in a significant reduction in malaria transmission in the Greater Accra Region.
Publisher: MDPI AG
Date: 22-09-2022
Abstract: Malaria remains a serious public health challenge in Ghana including the Greater Accra Region. This study aimed to quantify the spatial, temporal and spatio-temporal patterns of malaria in the Greater Accra Region to inform targeted allocation of health resources. Malaria cases data from 2015 to 2019 were obtained from the Ghanaian District Health Information and Management System and aggregated at a district and monthly level. Spatial analysis was conducted using the Global Moran’s I, Getis-Ord Gi*, and local indicators of spatial autocorrelation. Kulldorff’s space–time scan statistics were used to investigate space–time clustering. A negative binomial regression was used to find correlations between climatic factors and sociodemographic characteristics and the incidence of malaria. A total of 1,105,370 malaria cases were reported between 2015 and 2019. Significant seasonal variation was observed, with June and July being the peak months of reported malaria cases. The hotspots districts were Kpone-Katamanso Municipal District, Ashaiman Municipal Districts, Tema Municipal District, and La-Nkwantanang-Madina Municipal District. While La-Nkwantanang-Madina Municipal District was high-high cluster. The Spatio-temporal clusters occurred between February 2015 and July 2017 in the districts of Ningo-Pr ram, Shai-Osudoku, Ashaiman Municipal, and Kpone-Katamanso Municipal with a radius of 26.63 km and an relative risk of 4.66 (p 0.001). Malaria cases were positively associated with monthly rainfall (adjusted odds ratio [AOR] = 1.01 95% confidence interval [CI] = 1.005, 1.016) and the previous month’s cases (AOR = 1.064 95% CI 1.062, 1.065) and negatively correlated with minimum temperature (AOR = 0.86, 95% CI = 0.823, 0.899) and population density (AOR = 0.996, 95% CI = 0.994, 0.998). Malaria control and prevention should be strengthened in hotspot districts in the appropriate months to improve program effectiveness.
Publisher: MDPI AG
Date: 04-06-2021
Abstract: The Greater Accra Region is the smallest of the 16 administrative regions in Ghana. It is highly populated and characterized by tropical climatic conditions. Although efforts towards malaria control in Ghana have had positive impacts, malaria remains in the top five diseases reported at healthcare facilities within the Greater Accra Region. To further accelerate progress, analysis of regionally generated data is needed to inform control and management measures at this level. This study aimed to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation in malaria burden. Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System. Malaria cases were decomposed using seasonal-trend decomposition, based on locally weighted regression to analyze seasonality. A negative binomial regression model with a conditional autoregressive prior structure was used to quantify associations between climatic variables and malaria risk and spatial dependence. Posterior parameters were estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs s ling. A total of 1,105,370 malaria cases were recorded in the region from 2015 to 2019. The overall malaria incidence for the region was approximately 47 per 1000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern. Monthly malaria case incidence was found to decrease by 2.3% (95% credible interval: 0.7–4.2%) for each 1 °C increase in monthly minimum temperature. Only five districts located in the south-central part of the region had a malaria incidence rate lower than the regional average at % probability level. The distribution of malaria cases was heterogeneous, seasonal, and significantly associated with climatic variables. Targeted malaria control and prevention in high-risk districts at the appropriate time points could result in a significant reduction in malaria transmission in the Greater Accra Region.
No related grants have been discovered for Elorm Donkor.