Identifying deprived "slum" neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data.

Background: Identifying urban deprived areas, including slums, can facilitate more targeted planning and development policies in cities to reduce socio-economic and health inequities, but methods to identify them are often ad-hoc, resource intensive, and cannot keep pace with rapidly urbanizing communities. Objectives: We apply a spatial modelling approach to identify census enumeration areas (EAs) in the Greater Accra Metropolitan Area (GAMA) of Ghana with a high probability of being a deprived area using publicly available census and remote sensing data. Methods: We obtained United Nations (UN) supported field mapping data that identified deprived "slum" areas in Accra's urban core, data on housing and population conditions from the most recent census, and remotely sensed data on environmental conditions in the GAMA. We first fitted a Bayesian logistic regression model on the data in Accra's urban core (n=2,414 EAs) that estimated the relationship between housing, population, and environmental predictors and being a deprived area according to the UN's deprived area assessment. Using these relationships, we predicted the probability of being a deprived area for each of the 4,615 urban EAs in GAMA. Results: 899 (19%) of the 4,615 urban EAs in GAMA, with an estimated 745,714 residents (22% of its urban population), had a high predicted probability (≥80%) of being a deprived area. These deprived EAs were dispersed across GAMA and relatively heterogeneous in their housing and environmental conditions, but shared some common features including a higher population density, lower elevation and vegetation abundance, and less access to indoor piped water and sanitation. Conclusion: Our approach using ubiquitously available administrative and satellite data can be used to identify deprived neighbourhoods where interventions are warranted to improve living conditions, and track progress in achieving the Sustainable Development Goals aiming to reduce the population living in unsafe or vulnerable human settlements.

Epidemiology of invasive meningococcal disease in Canada, 2012-2019.

Background: A variety of routine childhood and adolescent meningococcal vaccination programs using monovalent (serogroup C) and quadrivalent (A, C, Y, W) conjugate vaccines have been implemented in Canada since 2002, resulting in a decrease in invasive meningococcal disease (IMD) incidence, particularly in serogroup C. Meningococcal vaccines have also been used for outbreak response, including the multicomponent vaccine serogroup B vaccine. This report describes the epidemiology of IMD in Canada from 2012 to 2019. Methods: Case data were obtained from the National Enhanced IMD Surveillance System between January 1, 2012 and December 31, 2019. Isolates were sent to the National Microbiology Laboratory for confirmation of serogroup and further studies including phenotype and clonal complex identification. Results: A total of 983 cases of IMD were reported between 2012 and 2019. Overall, the age-adjusted incidence of IMD from 2012 to 2019 was 0.34 cases per 100,000 population per year when standardized to the Canadian 2011 population age distribution (95% CI: 0.32-0.36). Infants younger than one year of age had the highest average age-specific incidence rate (3.6 cases per 100,000 population per year, 95% CI: 2.8-4.3). The highest age-adjusted incidence rate was associated with serogroup B (0.17 cases per 100, 000 population per year, 95% CI: 0.16-0.19). Prior to 2015, most invasive serogroup W isolates were identified as clonal complex 22 (ST-22 CC) and the increase in serogroup W in Canada in recent years has been associated with the replacement of the endemic ST-22 CC with the hyper-virulent ST-11 CC. Conclusion: Invasive meningococcal disease is a rare but severe infection in Canada that mostly affects the very young. Serogroup B continues to account for the greatest proportion of disease. Serogroup W associated with ST-11 CC is becoming a growing contributor of disease in all age groups not protected by serogroup W-containing vaccines.

Environmental Lead Exposure and Adult Literacy in Myanmar: An Exploratory Study of Potential Associations at the Township Level.

Environmental lead exposure is a population health concern in many low- and middle-income countries. Lead is found throughout Myanmar and prior to the 1940s the country was the largest producer of lead worldwide. The aim of this study was to examine any potential association between lead mining and adult literacy rates at the level of 330 townships in Myanmar. Townships were identified as lead or non-lead mining areas and 2015 census data were examined with association being identified using descriptive, analytical and spatial statistical methods. Overall, there does appear to be a significant relationship between lead mining activity and adult literacy levels among townships with both low access (p = 0.05; OR = 2.701 (1.136⁻6.421)) as well with high access to safe sanitation (p = 0.01; OR = 18.40 (1.794⁻188.745)). Local Indicators of Spatial Association (LISA) cluster maps confirm these findings. This exploratory analysis is a first step in the examination of potential environmental lead exposure and its implications in Myanmar.