15 research outputs found
Local population and regional environmental drivers of cholera in Bangladesh
<p>Abstract</p> <p>Background</p> <p>Regional environmental factors have been shown to be related to cholera. Previous work in Bangladesh found that temporal patterns of cholera are positively related to satellite-derived environmental variables including ocean chlorophyll concentration (OCC).</p> <p>Methods</p> <p>This paper investigates whether local socio-economic status (SES) modifies the effect of regional environmental forces. The study area is Matlab, Bangladesh, an area of approximately 200,000 people with an active health and demographic surveillance system. Study data include (1) spatially-referenced demographic and socio-economic characteristics of the population; (2) satellite-derived variables for sea surface temperature (SST), sea surface height (SSH), and OCC; and (3) laboratory confirmed cholera case data for the entire population. Relationships between cholera, the environmental variables, and SES are measured using generalized estimating equations with a logit link function. Additionally two separate seasonal models are built because there are two annual cholera epidemics, one pre-monsoon, and one post-monsoon.</p> <p>Results</p> <p>SES has a significant impact on cholera occurrence: the higher the SES score, the lower the occurrence of cholera. There is a significant negative association between cholera incidence and SSH during the pre-monsoon period but not for the post-monsoon period. OCC is positively associated with cholera during the pre-monsoon period but not for the post-monsoon period. SST is not related to cholera incidence.</p> <p>Conclusions</p> <p>Overall, it appears cholera is influenced by regional environmental variables during the pre-monsoon period and by local-level variables (e.g., water and sanitation) during the post-monsoon period. In both pre- and post-monsoon seasons, SES significantly influences these patterns, likely because it is a proxy for poor water quality and sanitation in poorer households.</p
The Role of Vaccine Coverage within Social Networks in Cholera Vaccine Efficacy
Traditional vaccine trial methods have an underlying assumption that the effect of a vaccine is the same throughout the trial area. There are, however, many spatial and behavioral factors that alter the rates of contact among infectious and susceptible individuals and result in different efficacies across a population. We reanalyzed data from a field trial in Bangladesh to ascertain whether there is evidence of indirect protection from cholera vaccines when vaccination rates are high in an individual's social network.We analyzed the first year of surveillance data from a placebo-controlled trial of B subunit-killed whole-cell and killed whole-cell-only oral cholera vaccines in children and adult women in Bangladesh. We calculated whether there was an inverse trend for the relation between the level of vaccine coverage in an individual's social network and the incidence of cholera in individual vaccine recipients or placebo recipients after controlling for potential confounding variables.Using bari-level social network ties, we found incidence rates of cholera among placebo recipients were inversely related to levels of vaccine coverage (5.28 cases per 1000 in the lowest quintile vs 3.27 cases per 1000 in the highest quintile; p = 0.037 for trend). Receipt of vaccine by an individual and the level of vaccine coverage of the individual's social network were independently related to a reduced risk of cholera.Findings indicate that progressively higher levels of vaccine coverage in bari-level social networks can lead to increasing levels of indirect protection of non-vaccinated individuals and could also lead to progressively higher levels of total protection of vaccine recipients
Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan
<p>Abstract</p> <p>Background</p> <p>Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan.</p> <p>Methods</p> <p>The statistical methods used were the global measures of Moran's <it>I </it>and Local Indicators of Spatial Association (LISA). While Moran's <it>I </it>provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level.</p> <p>Results</p> <p>The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas.</p> <p>Conclusions</p> <p>The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use.</p
Strengthening long-lasting insecticidal nets effectiveness monitoring using retrospective analysis of cross-sectional, population-based surveys across sub-Saharan Africa
Bed nets averted 68% of malaria cases in Africa between 2000 and 2015. However, concerns over insecticide resistance, bed net durability and the effectiveness of long-lasting insecticidal nets (LLIN) are growing. To assess the effectiveness of LLINs of different ages and insecticides against malaria, we conducted a population-based, cross-sectional study using data from 162,963 children younger than 5 years of age participating in 33 Demographic and Health and Malaria Indicator Surveys conducted in 21 countries between 2009 and 2016. We used Bayesian logistic regression to estimate associations between LLIN age, insecticide type, and malaria. Children sleeping under LLINs the previous night experienced 21% lower odds of malaria infection than children who did not (odds ratio [OR] 0.79; 95% Uncertainty Interval [UI] 0.76–0.82). Nets less than one year of age exhibited the strongest protective effect (OR 0.75; 95% UI 0.72–0.79), and protection weakened as net age increased. LLINs containing different insecticides exhibited similar protection (ORdeltamethrin 0.78 [0.75–0.82]; ORpermethrin 0.79 [0.75–0.83]; ORalphacypermethrin 0.85 [0.76–0.94]). Freely-available, population-based surveys can enhance and guide current entomological monitoring amid concerns of insecticide resistance and bed net durability, and be used with locally-collected data to support decisions on LLIN redistribution campaign timing which insecticide to use
Computational identification of reassortments in avian influenza viruses
The avian influenza virus (AIV) has eight genomic segments (hemagglutinin [HA], neuraminidase [NA], RNA polymerase subunit A [PA], RNA polymerase subunit B1 [PB1], RNA polymerase subunit B2 [PB2], nucleoprotein [NP], nonstructural gene [NS], and matrix protein [M]). The genetic reassortments, recombinations, and mutations lead to a rapid emergence of novel genotypes of the AIVs during their evolution. These emerging viruses provide a large reservoir for pandemic strains. Here we describe a novel computational strategy for genetic reassortment identification. In contrast to the traditional phylogenetic approaches, our method views the genotypes through the modules in networks. Genetic segments with short phylogenetic distance are grouped into modules. Our method is not limited to the number of sequences. We applied this method in reassortment identification of NP segments in H5N1 AIVs. We identified two new potential reassortments for H5N, AIVs beyond the reported genotypes in literature.link_to_subscribed_fulltex