An estimated 250 million children under five fail to reach their cognitive development potential in Africa. Growing evidence suggests reduced neurodevelopments for children from environmental exposures, yet research on this topic in Sub-Saharan Africa remains limited. This study examined the effects of multi-chemical prenatal exposure to heavy metals on developmental milestones for children aged 3–4 in artisanal and small gold mining areas in northwestern Tanzania. This longitudinal follow-up study of children whose mothers were enrolled in the Tanzania Mining and Health Cohort in Geita District in 2015 were assessed at 3–4 years of age for the current study between June 2019 – June 2020. Developmental outcomes (cognitive, social, motor, and language skills) were assessed using the Malawi Developmental Assessment Tool (MDAT). A quantile g-computation model evaluated the linkage between multi-chemical exposures and developmental milestones. Of the 310 children in the follow-up, a majority had at least one form of developmental impairment (50.7%; n = 157) across four domains: gross motor (20.3%), fine motor (23.9%), language (28.3%), and social skill (16.2%). Increased Pb, Hg, Cd, and As exposure jointly reduced gross motor by 17.78% (aPR = 0.822; 95% CI: 0.6994, 0.966). Joint exposure to these heavy metals decreased language ability by 55.36% (aPR = 0.446; 95% CI: 0.313, 0.636) and decreased general developmental milestones by 13.36% (aPR = 0.866; 95% CI: 0.747,1.005). However, the combined effect on the fine motor (aPR = 0.943; 95% CI: 0.754, 1.180) and social skills 6.71% (aPR = 1.067; 95% CI: 0.694, 1.641) were not statistically significant. Exposure to heavy metals while in utero reduced children neurodevelopmental milestones at 3–4 years of age. The cumulative impact of Pb, Hg, Cd, and As was significant for gross motor, language ability, and general impairment. The independent effects of Pb and Hg were amplified beyond what would be expected under the additive assumption with Cd and As, suggesting synergistic effects.

Purpose: The study aimed to use geographic information system (GIS) based multi-criteria decision making analysis (GIS-MCDA) to select areas suitable for siting landfills in Ashanti region. It also sought to ascertain variables most sensitive to the siting of landfill in the region.Design/methodology/approach: This study utilized GIS-based Multi-criteria decision making analysis –AHP to model and select areas most suitable to siting landfills within the region. Overall, 16 variables including wind speed and hydraulic conductivity (which were previously neglected in landfill siting in Ghana) were identified through comprehensive literature review. These variables were weighted using AHP method and integrated using the weighted linear combination (WLC) in GIS environment to develop five sub-models: the physical environmental, sociocultural, economic/technical, climatic and hydrogeological sub-models. These sub-models were further weighted and then integrated to derive the final suitability model.Findings: Results show that 13% (3,067 km²) of the region was identified as most suitable to siting engineered landfills. The study also identified 11 sites which are considered most suitable for situating landfills. On a sensitivity angle, hydrogeological (R² = 0.5923; p = 0.003) and physical environmental sub-model (R² = 0.254; p = 0.034) significantly predicted the final suitability model developed.Practical implications: Ghana's Landfill Guidelines seeks to optimize site selection and ancillary services that culminate into achieving sanitary landfills by 2020. Evidence still abounds on the unsuitability of existing and in some cases, new landfill sites presenting environmental and social negative impacts. The comprehensive evaluation of most crucial variables – social and environmental factors that determine an optimal landfill location – will be of immense help to policy planners like the Environmental Protection Agency (EPA) towards upgraded landfills. The authors hope that, concerned agencies will adopt the model in the study and integrate into their existing landfill suitability modeling techniques to provide a more grounded framework that optimizes landfill site selection within the study area.Originality/value: This study is the first attempt to consider a regional-level waste collection site selection in Ghana using comprehensive sets of social and environmental factors and will therefore contribute immensely to EPA's goal of achieving upgraded landfills by 2022.

Cholera, which is caused byVibrio cholerae, persists as a devastating acute diarrheal disease. Despite availability of information on socio-cultural, agent and hosts risk factors, the disease continues to claim lives of people in Tanzania. The present study explores spatial patterns of cholera cases during a 2015–16 outbreak in Mwanza, Tanzania using a geographical information system (GIS) to identify concentrations of cholera cases. This cross-sectional study was conducted in Ilemela and Nyamagana Districts, Mwanza City. The two-phase data collection included: 1) retrospectively reviewing and capturing 852 suspected cholera cases from clinical files during the outbreak between August, 2015, and April, 2016, and 2) mapping of residence of suspected and confirmed cholera cases using global positioning systems (GPS). A majority of cholera patients were from Ilemela District (546, 64.1%), were males (506, 59.4%) and their median age was 27 (19–36) years. Of the 452 (55.1%) laboratory tests, 352 (77.9%) were confirmed to haveVibrio choleraeinfection. Seven patients (0.80%) died. Cholera cases clustered in certain areas of Mwanza City. Sangabuye, Bugogwa and Igoma Wards had the largest number of confirmed cholera cases, while Luchelele Ward had no reported cholera cases. Concentrations may reflect health-seeking behavior as much as disease distribution. Topographical terrain, untreated water, physical and built environment, and health-seeking behaviors play a role in cholera epidemic in Mwanza City. The spatial analysis suggests patterns of health-seeking behavior more than patterns of disease. Maps similar to those generated in this study would be an important future resource for identifying an impending cholera outbreak in real-time to coordinate community members, community leaders and health personnel for guiding targeted education, outreach, and interventions.