RESUMEN
We retrospectively analyzed spatial factors for coronavirus disease 2019 (COVID-19)-associated community deaths i.e., brought-in-dead (BID) in Lusaka, Zambia, between March and July 2020. A total of 127 cases of BID with geocoordinate data of their houses were identified during the study period. Median interquartile range (IQR) of the age of these cases was 49 (34-70) years old, and 47 cases (37.0%) were elderly individuals over 60 years old. Seventy-five cases (75%) of BID were identified in July 2020, when the total number of cases and deaths was largest in Zambia. Among those whose information regarding their underlying medical condition was available, hypertension was most common (22.9%, 8/35). Among Lusaka's 94 townships, the numbers (median, IQR) of cases were significantly larger in those characterized as unplanned residential areas compared to planned areas (1.0, 0.0-4.0 vs 0.0, 0.0-1.0; p=0.030). The proportion of individuals who require more than 30 minutes to obtain water was correlated with a larger number of BID cases per 105 population in each township (rho=0.28, p=0.006). The number of BID cases was larger in unplanned residential areas, which highlighted the importance of targeted public health interventions specifically to those areas to reduce the total number of COVID-19 associated community deaths in Lusaka. Brought-in-dead surveillance might be beneficial in monitoring epidemic conditions of COVID-19 in such high-risk areas. Furthermore, inadequate access to water, sanitation, and hygiene (WASH) might be associated with such distinct geographical distributions of COVID-19 associated community deaths in Lusaka, Zambia.
Asunto(s)
COVID-19 , Humanos , Anciano , Persona de Mediana Edad , Estudios Retrospectivos , Zambia/epidemiología , Agua , HigieneRESUMEN
BACKGROUND: The outbreak of West Nile Virus (WNV) in and around Chicago in 2002 included over 680 cases of human illness caused by the virus within this region. The notable clustering of the cases in two well-defined areas suggests the existence of specific environmental and social factors that increase the risk for WNV infection and/or illness in these locations. This investigation sought to create an empirically based model to account for these factors and to assess their importance in explaining the possible processes that may have led to this pattern. RESULTS: The cluster pattern of high incidence of cases was statistically significant. The risk factors that were found to be important included the presence of vegetation, age, income, and race of the human population, distance to a WNV positive dead bird specimen, age of housing, mosquito abatement and geological factors. The effect of different mosquito abatement efforts was particularly notable. About 53 percent of the variation of the location of WNV clusters was explained by these factors. CONCLUSION: The models developed indicate that differential mosquito abatement efforts are especially important risk factors, even when controlling for key environmental factors. Human population characteristics play a role in risk that is measurable in this ecological study but would require further research to associate causality with risk. The analysis of spatial clusters of case incidence indicates that this approach provides more insight into the focal nature of differential risk factors that tend to be associated with WNV than an analysis of all individual cases.
RESUMEN
Differences in mosquito control practices at the local level involve the interplay of place, scale and politics. During the Chicago West Nile Virus (WNV) outbreak of 2002, mosquito abatement districts represent distinct suburban clusters of human WNV cases, independent of characteristics of the local population, housing and physical environment. We examine how the contrasting actions of four districts reveal a distinct local politics of mosquito control that may have contributed to local-scale geographic differences in WNV incidence. This politics is rooted in political, economic and philosophical differences within and between administrative boundaries.