Spatial Demography最新文献

Childhood diarrhoea accounts for over 15% of all under-five deaths in Africa. The disease is exacerbated by social vulnerability. This study operationalizes social vulnerability by using three indicators: water poverty, sanitation and assets, to capture social disadvantage, which measures individual or community resources to prevent or mitigate health effects. We particularly investigated the relationship between childhood diarrhoea and risks emanating from multiple stressors: water poverty, poor sanitation and low wealth status, which define social vulnerability. Using data from the 2013/14 Malawi MDG Endline Survey (MMES), we fitted spatial models assuming that the combined effect of social vulnerability indicators, together with individual covariates, exhibit spatial correlation and heterogeneity on the outcome-diarrhoea status. Findings showed evidence of spatially varying risk imposed by social vulnerability indicators on childhood diarrhoea. We established a positive relationship between diarrhoea and water poverty, and negative association with poor sanitation and low wealth status. Spatial characterization of health effects of social vulnerability presents an important step towards targeted interventions in diarrhoea management. Our use of district level mapping provides for optimal planning and implementation, particularly, for the lowly placed individuals who are geographically located in high risk areas, since most decentralized decision making processes are made at this level.

Small area population forecasts are widely used across the public and private sectors, with many users requiring forecasts broken down by sex and age group. The preparation of small area age-sex population forecasts across a whole country or State with a multiregional cohort-component model is usually a time-consuming and expensive task. It involves the purchase of large datasets, considerable amounts of complex data preparation and assumption-setting, and substantial amounts of staff time. A quicker and lower-cost alternative is to use a reduced form cohort projection model, such as the Hamilton-Perry model. This paper presents an evaluation of various implementations of the Hamilton-Perry model, including an alternative version employing a combination of Cohort Change Ratios and Cohort Change Differences. It also evaluates the effects on forecast accuracy of smoothing the age profiles of Cohort Change Ratios and Differences, and constraining to independent population forecasts. Population ‘forecasts’ were created for small areas of Australia over the horizon 2006–16 and compared against population estimates. The most accurate implementation is found to be the Hamilton-Perry model using a combination of Cohort Change Ratios and Cohort Change Differences, smoothed age profiles, and with constraining to independent forecasts.

The early stages of the COVID-19 pandemic required a dramatic change in social practices, including distancing from social settings, to limit its spread. While social capital has considerable potential in facilitating the adoption of these norms, it also comes with considerable limitations that potentially undermine its effectiveness. We draw upon recently released mobility data from Google, network data from Facebook, and demographic data from the 2018 American Community Survey to determine how both organizational and networked measures of social capital relate to different forms of distancing. In addition, we employ geographically weighted regression to identify how these relationships vary across the nation. Findings indicate that while both forms of social capital can positively relate to distancing, the impacts are spatially inconsistent and, in some locations, social capital can discourage distancing. In sum, more policy efforts are needed to address not only low-social capital, but also unhelpful social capital.

Subsequent to the arrival of SARS-CoV-2 and emergence of COVID-19, policy to limit the further spread has focused on increasing distance between individuals when interacting, often termed social distancing although physical distancing is more accurate (Das Gupta and Wong in Canadian J Public Health 111:488-489, 2020; Gale in Is 'social distancing' the wrong term? Expert prefers 'physical distancing,' and the WHO agrees. The Washington Post, 2020; Sørensen et al. in Glob Health Promot, 28:5-14, 2021), and limiting the frequency of interaction by limiting/prohibiting non-essential and large-scale social gatherings. This research note focuses on social spacing, defined by distance and interaction, to offer a cross-cultural insight into social distancing and social interactions in the pre-pandemic period. Combining unique data on frequency of contact, religious service attendance and preferred interpersonal spacing in 20 countries, this research note considers variation in the extent to which physical distance was already practiced without official recommendations and underscores notable cross-cultural variation in the extent to which social interaction occurred. Results suggest that policy intervention should emphasize certain behavioral changes based on pre-existing context-specific patterns of interaction and interpersonal spacing rather than a one-size-fits-all approach. This research note is a descriptive first step that allows unique insight into social spacing and contact prior to the spread of SARS-CoV-2. It provides a baseline typology and a reference for future work on the cross-cultural implications of COVID-19 for pre-pandemic socio-cultural practice and vice versa.