Seasonal and spatial variations of malaria transmissions in northwest Ethiopia: Evaluating climate and environmental effects using generalized additive model.

The impacts of climate change and environmental predictors on malaria epidemiology remain unclear and not well investigated in the Sub-Sahara African region. This study was aimed to investigate the nonlinear effects of climate and environmental factors on monthly malaria cases in northwest Ethiopia, considering space-time interaction effects. The monthly malaria cases and populations sizes of the 152 districts were obtained from the Amhara public health institute and the central statistical agency of Ethiopia. The climate and environmental data were retrieved from US National Oceanic and Atmospheric Administration. The data were analyzed using a spatiotemporal generalized additive model. The spatial, temporal, and space-time interaction effects had higher contributions in explaining the spatiotemporal distribution of malaria transmissions. Malaria transmission was seasonal, in which a higher number of cases occurred from September to November. The long-term trend of malaria incidence has decreased between 2012 and 2018 and has turned to an increased pattern since 2019. Areas neighborhood to the Abay gorge and Benshangul-Gumuz, South Sudan, and Sudan border have higher spatial effects. Climate and environmental predictors had significant nonlinear effects, in which their effects are not stationary through the ranges of values of variables, and they had a smaller contributions in explaining the variabilities of malaria incidence compared to seasonal, spatial and temporal effects. Effects of climate and environmental predictors were nonlinear and varied across areas, ecology, and landscape of the study sites, which had little contribution to explaining malaria transmission variabilities with an account of space and time dimensions. Hence, exploring and developing an early warning system that predicts the outbreak of malaria transmission would have an essential role in controlling, preventing, and eliminating malaria in areas with lower and higher transmission levels and ultimately lead to the achievement of malaria GTS milestones.

Detection of temporal, spatial and spatiotemporal clustering of malaria incidence in northwest Ethiopia, 2012-2020.

Malaria is one of Ethiopia's most targeted communicable diseases for elimination. Malaria transmission varies significantly across space and time; and Ethiopia had space-time disparity in its transmission intensities. Considering heterogeneity and transmission intensity at the district level could play a crucial role in malaria prevention and elimination. This study aimed to explore temporal, spatial, and spatiotemporal clusters of malaria incidence in northwest Ethiopia. The analysis is based on monthly malaria surveillance data of districts and collected from the Amhara public health institute. The Kulldorff's retrospective space-time scan statistics using a discrete Poisson model were used to detect temporal, spatial, and space-time clusters of malaria incidence with and without adjusting the altitude + LLIN arm. Monthly malaria incidence had seasonal variations, and higher seasonal indices occurred in October and November. The temporal cluster occurred in the higher transmission season between September and December annually. The higher malaria incidence risk occurred between July 2012 and December 2013 (LLR = 414,013.41, RR = 2.54, P < 0.05). The purely spatial clustering result revealed that the most likely cluster occurred in the north and northwest parts of the region while secondary clusters varied in years. The space-time clusters were detected with and without considering altitude + LLIN arm. The most likely space-time cluster was concentrated in northwestern and western parts of the region with a high-risk period between July 2012 and December 2013 (LLR = 880,088.3, RR = 5.5, P < 0.001). We found eight significant space-time clusters using the altitude + LLIN arm. The most likely space-time cluster occurred in the western and northwestern parts of the region in July 2012-December 2013 (LLR = 886,097.7, RR = 5.55, P < 0.05). However, secondary clusters were located in eastern, northwestern, western parts of regions, which had different cases and relative risks in each cluster. Malaria transmission had temporal, spatial, and space-time variation in the region at the district level. Hence, considering these variations and factors contributing to malaria stratification would play an indispensable role in preventing and controlling practices that ultimately leads to malaria eliminations.

Effects of climate variability and environmental factors on the spatiotemporal distribution of malaria incidence in the Amhara national regional state, Ethiopia.

Malaria is a severe public health problem in the Amhara region, Ethiopia. A retrospective study was conducted to model and interpret the effects of climate variability and environmental factors on the monthly malaria surveillance data of 152 districts in the region. The data were analyzed using the Bayesian generalized Poisson spatiotemporal model. Malaria incidence had significant seasonal, temporal, and spatial variations in the region. The risk of malaria incidence was decreased by 24% per 100 m increase in altitude. Monthly minimum temperature decreases the risk of malaria by 2.2% per a 1°C increment. The risk of malaria transmission was increased by 8% per 100 mm rise in the total monthly rainfall of districts. Besides, long-lasting insecticidal net coverage significantly reduces malaria risk by a factor of 0.8955. The finding suggests that malaria transmission was higher in northern and western districts. Hence, concerned bodies should consider seasonal, temporal, and spatial variations and effects of climate and environmental factors for intervention and elimination.

Spatiotemporal Trends and Distributions of Malaria Incidence in the Northwest Ethiopia.

Understanding and extracting noticeable patterns of malaria surveillance data at the district level are crucial for malaria prevention, control, and elimination progress. This study aimed to analyze spatiotemporal trends and nonparametric dynamics of malaria incidences in northwest Ethiopia, considering spatial and temporal correlations. The data were analyzed using count regression spatiotemporal models under the Bayesian setups, and parameters were estimated using integrated nested Laplace approximations (INLA). The region had a declining linear trend, and the average annual malaria incidence rate was 24.8 per 1,000 persons between 2012 and 2020. The malaria incidence rate was decreased by 0.984 (95% CI: 0.983, 0.986) per unit increase in months between July 2012 and June 2020. Districts found in the western and northwestern parts of the region had a steeper trend, while districts in the eastern and southern parts had a less steep trend than the average trend of the region. Compared to the regional level trend, the decreasing rate of malaria incidence trends was lower in most town administrations. The nonparametric dynamics showed that the monthly malaria incidence had a sinusoidal wave shape that varied throughout study periods. Malaria incidence had a decreasing linear trend changed across districts of the study region, and the steepness of trends of districts might not depend on incidences. Thus, an intervention and controlling mechanism that considers malaria incidences and district-specific differential trends would be indispensable to mitigate malaria transmission in the region.

Factors associated with childhood diarrheal in Ethiopia; a multilevel analysis.

BACKGROUND: Diarrhea is the second cause of child deaths globally. According to World Health Organization reports, in each year it kills more than 525,000 children under-5 years. More than half of these deaths occur in five countries including Ethiopia. This study aimed to identify both individual and community-level risk factors of childhood diarrheal in Ethiopia. METHODS: Ethiopian demography and health survey of 2016 data were used for the analysis. A total of 10,641 children aged 0-59 months were included in the analysis. A multi-level mixed-effect logistic regression model was used to identify both individual and community-level risk factors associated with childhood diarrheal. RESULT: The incidence of childhood diarrheal was 12% (95%CI: 11.39, 12.63). The random effect model revealed that 67% of the variability of childhood diarrhea explained by individual and community level factors. From the individual-level factors, children aged 36-59 month (AOR = 3.166; 95% CI: 2.569, 3.900), twin child (AOR = 1.871; 95% CI: 1.390, 2.527), birth order 5 and above (AOR = 2.210, 95% CI: 1.721, 2.839), not received any vaccination (AOR = 1.197; 95% CI: 1.190,1.527), smaller size of child at birth (AOR = 1.303;95% CI: 1.130,1.504) and never breastfed children (AOR = 2.91;95%CI:2.380,3.567) associated with the higher incidence of childhood diarrhea. From the community-level factors, living in a rural area ((AOR = 1.505; 95%CI: 1.233, 1.836)), unprotected source of drinking water (AOR: 1.289; 95% CI: 1.060, 1.567) and availability of unimproved latrine facilities (OR: 1.289; 95% CI: 1.239, 1.759) associated with the higher incidence of childhood diarrhea. Besides, Children live in Afar, Amhara, Benishangul-Gumuz, Gambella, SNNPR and Dire Dawa regions had higher incidence of childhood diarrhea. CONCLUSION: The incidence of childhood diarrhea was different from cluster to clusters in Ethiopia. Therefore, integrated child health intervention programs including provisions of toilet facility, access to a clean source of drinking water, educate parents about the importance of breastfeeding and vaccination have to be strongly implemented in order to reduce the high incidence of childhood diarrhea among children in Ethiopia.

Individual- and Community-Level Risk Factors Associated with Childhood Diarrhea in Ethiopia: A Multilevel Analysis of 2016 Ethiopia Demographic and Health Survey.

BACKGROUND: Diarrhea is the second cause of child deaths globally. According to World Health Organization reports, in each year, it kills more than 525,000 children under 5 years. More than half of these deaths occur in five countries including Ethiopia. This study is aimed at identifying both individual- and community-level risk factors of childhood diarrhea in Ethiopia. METHODS: Ethiopian demography and health survey of 2016 data were used for the analysis. A total of 10,641 children aged 0-59 months were included in the analysis. A multilevel mixed-effects logistic regression model was used to identify both individual- and community-level risk factors associated with childhood diarrhea. RESULT: The incidence of childhood diarrhea was 12% (95% CI: 11.39, 12.63). The random-effects model revealed that 67% of the variability of childhood diarrhea was explained by individual- and community-level factors. From the individual-level factors, children aged 36-59 months (AOR = 3.166; 95% CI: 2.569, 3.900), twin child (AOR = 1.871; 95% CI: 1.390, 2.527), birth order 5 and above (AOR = 2.210, 95% CI: 1.721, 2.839), not received any vaccination (AOR = 1.197; 95% CI: 1.190, 1.527), smaller size of child at birth (AOR = 1.303; 95% CI: 1.130, 1.504), and never breastfed children (AOR = 2.91; 95% CI: 2.380, 3.567) associated with the higher incidence of childhood diarrhea. From the community-level factors, living in a rural area (AOR = 1.505; 95% CI: 1.233, 1.836)), unprotected source of drinking water (AOR = 1.289; 95% CI: 1.060, 1.567), and availability of unimproved latrine facilities (OR: 1.289; 95% CI: 1.239, 1.759) associated with the higher incidence of childhood diarrhea. Besides, children who live in Afar, Amhara, Benishangul-Gumuz, Gambella, SNNPR, and Dire Dawa regions had higher incidence of childhood diarrhea. CONCLUSION: The incidence of childhood diarrhea was different from cluster to cluster in Ethiopia. Therefore, integrated child health intervention programs including provisions of toilet facility, access to a clean source of drinking water, educate parents about the importance of breastfeeding, and vaccination have to be strongly implemented in order to reduce the high incidence of childhood diarrhea among children in Ethiopia.