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Background: One of the main factors contributing to maternal morbidity and mortality is induced abortion. The WHO estimates that over 44 million induced abortions take place annually around the world. The majority of these abortions—about 50%—are unsafe, significantly increasing maternal morbidity and contributing to 13% of maternal deaths. Thus, this review aimed to estimate the pooled prevalence of induced abortion and its associated factors in Africa. Methods: To find literature on the prevalence of induced abortion and its associated factors, a thorough search of the internet databases such as PubMed/MEDLINE, African Journals Online, and Google Scholar was conducted. The data were extracted using a structured method of data collection. Software called STATA 14 was used to do the analysis. funnel plot and Egger regression test were used to evaluate potential publication bias. I2 statistics and Cochrane's Q were used to measure the heterogeneity at a p-value < 0.05. Results: 976 studies were found through a thorough search of electronic databases. Finally, 46 full-text abstract papers were included in this study. The estimated pooled prevalence of induced abortion was 16% (95% CI: 13%-19%). According to the sub-group analysis, most studies were conducted in Ethiopia, and the pooled prevalence was 19% (95% CI: 10%–30%). Similarly, the subgroup analysis by year of study showed that the prevalence of induced abortion was 39% (95% CI: 17%–64%) among studies conducted in 2019. Conclusion: The results of this study thus imply that the pooled prevalence of induced abortion is higher than that of earlier studies that were published in some nations. the data from this study are needed to support reproductive and adolescent health programmers and policymakers and to formulate recommendations for future clinical practice and guidelines. [ABSTRACT FROM AUTHOR]

Since 2016, fall armyworm (FAW) has threatened sub-Saharan 'Africa's fragile food systems and economic performance. Yet, there is limited evidence on this transboundary pest's economic and food security impacts in the region. Additionally, the health and environmental consequences of the insecticides being used to control FAW have not been studied. This paper presents evidence on the impacts of FAW on maize production, food security, and human and environmental health. We use a combination of an agroecology-based community survey and nationally representative data from an agricultural household survey to achieve our objectives. The results indicate that the pest causes an average annual loss of 36% in maize production, reducing 0.67 million tonnes of maize (0.225 million tonnes per year) between 2017 and 2019. The total economic loss is US$ 200 million, or 0.08% of the gross domestic product. The lost production could have met the per capita maize consumption of 4 million people. We also find that insecticides to control FAW have more significant toxic effects on the environment than on humans. This paper highlights governments and development partners need to invest in sustainable FAW control strategies to reduce maize production loss, improve food security, and protect human and environmental health. [ABSTRACT FROM AUTHOR]

Background: Geospatial data are important in monitoring many aspects of healthcare development. Geographically linking health facility data with population data is an important area of public health research. Examining healthcare problems spatially and hierarchically assists with efficient resource allocation and the monitoring and evaluation of service efficacy at different levels. This paper explored methodological issues associated with geographic data linkage, and the spatial and multilevel analyses that could be considered in analysing maternal health service data. Methods: The 2016 Ethiopia Demographic and Health Survey and the 2014 Ethiopia Service Provision Assessment data were used. Two geographic data linking methods were used to link these two datasets. Administrative boundary link was used to link a sample of health facilities data with population survey data for analysing three areas of maternal health service use. Euclidean buffer link was used for a census of hospitals to analyse caesarean delivery use in Ethiopia. The Global Moran’s I and the Getis-Ord Gi* statistics need to be carried out for identifying hot spots of maternal health service use in ArcGIS software. In addition to this, since the two datasets contain hierarchical data, a multilevel analysis was carried out to identify key determinants of maternal health service use in Ethiopia. Results: Administrative boundary link gave more types of health facilities and more maternal health services as compared to the Euclidean buffer link. Administrative boundary link is the method of choice in case of sampled health facilities. However, for a census of health facilities, the Euclidean buffer link is the appropriate choice as this provides cluster level service environment estimates, which the administrative boundary link does not. Applying a False Discovery Rate correction enables the identification of true spatial clusters of maternal health service use. Conclusions: A service environment link minimizes the methodological issues associated with geographic data linkage. A False Discovery Rate correction needs to be used to account for multiple and dependent testing while carrying out local spatial statistics. Examining maternal health service use both spatially and hierarchically has tremendous importance for identifying geographic areas that need special emphasis and for intervention purposes. [ABSTRACT FROM AUTHOR]