Spread of COVID-19 in urban neighbourhoods and slums of the developing world

We study the spread of COVID-19 across neighbourhoods of cities in the developing world and find that small numbers of neighbourhoods account for a majority of cases ( k -index approx. 0.7). We also find that the countrywide distribution of cases across states/provinces in these nations also displays similar inequality, indicating self-similarity across scales. Neighbourhoods with slums are found to contain the highest density of cases across all cities under consideration, revealing that slums constitute the most at-risk urban locations in this epidemic. We present a stochastic network model to study the spread of a respiratory epidemic through physically proximate and accidental daily human contacts in a city, and simulate outcomes for a city with two kinds of neighbourhoods—slum and non-slum. The model reproduces observed empirical outcomes for a broad set of parameter values—reflecting the potential validity of these findings for epidemic spread in general, especially across cities of the developing world. We also find that distribution of cases becomes less unequal as the epidemic runs its course, and that both peak and cumulative caseloads are worse for slum neighbourhoods than non-slums at the end of an epidemic. Large slums in the developing world, therefore, contain the most vulnerable populations in an outbreak, and the continuing growth of metropolises in Asia and Africa presents significant challenges for future respiratory outbreaks from perspectives of public health and socioeconomic equity.

Abstract 138: Socioeconomically Equitable Public Defibrillator Placement Using Mathematical Optimization

Introduction: Mathematical optimization can be used to place automated external defibrillators (AEDs) in locations that maximize coverage of out-of-hospital cardiac arrests (OHCAs). However, the extent to which optimization strategies affect socioeconomically equitable distribution of AEDs is unknown. Methods: All suspected OHCAs and registered AEDs in Scotland between Jan. 2011 - Sept. 2017 with a recorded location were included and mapped across the quintiles of the Scottish Index of Multiple Deprivation (SIMD), a national measure of socioeconomic status. First, we maintained AEDs at current locations and modeled placing an equal number of additional AEDs to maximize “coverage” (i.e., AED located within 100 m) of suspected OHCAs. A second analysis determined optimal sites for relocating all existing AEDs to optimize coverage without additional AEDs. We computed the proportion of OHCAs covered in each SIMD quintile under each AED placement strategy. A Wilcoxon signed-rank test was used to test difference in coverage levels across all regions of Scotland. Results: We identified 49,692 suspected OHCAs and 1,532 AEDs. Existing AEDs covered 1,384 OHCAs (2.8%), with OHCA coverage peaking in quintile 3 (moderate deprivation), indicating a mismatch with the distribution of suspected OHCA. Adding an equal number of new AEDs in optimal locations covered 10,465 OHCAs (21.1%; P<0.001). Optimal relocation of existing AEDs with no additional units covered 9,464 OHCAs (19.0%; P<0.001). OHCA coverage under either optimization strategy peaked in quintile 1 (highest deprivation), aligning to the OHCA incidence distribution. Conclusion: Optimizing AED placement significantly increases OHCA coverage and better aligns coverage with OHCA incidence across SIMD quintiles, improving socioeconomic equity of OHCA coverage. Relocating existing AEDs could achieve similar coverage to doubling the number of devices.

Socioeconomic inequalities in reach, compliance and effectiveness of lifestyle interventions among workers: protocol for an individual participant data meta-analysis and equity-specific reanalysis

IntroductionObesity and unhealthy behaviour are more prevalent among workers with a low compared with a high socioeconomic position (SEP), and thus contribute to socioeconomic health inequalities. The occupational setting is considered an important setting to address unhealthy behaviours due to the possibility to efficiently reach a large group of adults through worksite health promotion. This paper describes the rationale and design for an individual participant data (IPD) meta-analysis and a socioeconomic equity-specific reanalysis aiming to: (1) investigate socioeconomic differences in the effectiveness of interventions aimed at promoting healthy behaviour and preventing obesity, (2) examine socioeconomic differences in reach and compliance and (3) to investigate underlying factors affecting possible socioeconomic differences.Methods and analysisA systematic search was conducted in electronic databases including Embase, Medline Ovid, Web of Science, Cochrane Central and Google Scholar as well as in grey literature and trial registries. Two researchers have independently selected a total of 34 relevant studies (from 88 articles). Responsible researchers of these eligible studies were asked to provide their study data and an assessment of the methodological criteria was done. The data of the intervention studies will be pooled for the IPD meta-analysis, whereas the socioeconomic equity-specific reanalysis will focus on each study separately, stratified for SEP. Both methods will be conducted to investigate socioeconomic differences in effectiveness, reach and compliance (research aims 1 and 2). For research aim 3, different factors, such as population characteristics, organisational work environment and intervention characteristics, will be investigated as possible moderators in the associations between SEP and effectiveness, reach and compliance.Ethics and disseminationThe Medical Ethical Committee of Erasmus MC declared that the Medical Research Involving Human Subjects Act does not apply to the meta-analyses. The findings will be disseminated through peer-reviewed publications and (inter)national conference presentations.Trial registration numberCRD42018099878.