Summary Interference occurs when the treatment of one person affects the outcome of another. For example, in infectious diseases, whether one individual is vaccinated may affect whether another individual becomes infected or develops disease. Quantifying such indirect (or spillover) effects of vaccination could have important public health or policy implications. In this paper we use recently developed inverse-probability weighted (IPW) estimators of treatment effects in the presence of interference to analyze an individually-randomized, placebo-controlled trial of cholera vaccination that targeted 121,982 individuals in Matlab, Bangladesh. Because these IPW estimators have not been employed previously, a simulation study was also conducted to assess the empirical behavior of the estimators in settings similar to the cholera vaccine trial. Simulation study results demonstrate the IPW estimators can yield unbiased estimates of the direct, indirect, total and overall effects of vaccination when there is interference provided the untestable no unmeasured confounders assumption holds and the group-level propensity score model is correctly specified. Application of the IPW estimators to the cholera vaccine trial indicates the presence of interference. For example, the IPW estimates suggest on average 5.29 fewer cases of cholera per 1000 person-years (95% confidence interval 2.61, 7.96) will occur among unvaccinated individuals within neighborhoods with 60% vaccine coverage compared to neighborhoods with 32% coverage. Our analysis also demonstrates how not accounting for interference can render misleading conclusions about the public health utility of vaccination.
With this paper we explore the sensitivity of study results to spatial displacements associated with Demographic and Health Survey (DHS) data in research that integrates ancillary raster data. Through simulation studies, we found that the impact of DHS point displacements on raster-based analyses can be moderated through the generation of covariates representing average values from neighborhood buffers. Additionally, raster surface characteristics (i.e., spatial smoothness) were found to affect the extent of bias introduced through point displacements. Although simple point extraction produced unbiased estimates in analyses involving smooth continuous surfaces, it is not recommended in analyses that involve categorical raster surfaces.
This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The paper first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database which consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties between households using a complete network design and distance matrices are also created to model spatial relationships. Moran's I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects-spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always clusters in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases however kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study has offered several strategies on how.
Background Testing for high-risk human papillomavirus (HPV) infection using mailed, self-collected samples is a promising approach to increase screening in women who do not attend clinic screening at recommended intervals. Methods To assess this intervention among high-risk women in the United States, 429 women without a Papanicolaou (Pap) test in 4 or more years (overdue by US guidelines) were recruited from the general population. Participants aged 30 to 65 years were mailed a kit to self-collect a cervicovaginal sample at home, return the sample by mail, and receive HPV results by telephone, with referral to follow-up cytological Pap testing at a local clinic. Cervicovaginal self-samples were collected with a Viba brush, stored in Scope mouthwash, and tested by Hybrid Capture 2. Data were collected in 2010 to 2011 and analyzed in 2017. Results Two-thirds (64%) of participants returned a self-collected sample, of whom 15% tested HPV DNA positive. Human papillomavirus self-test–positive women reported higher rates of follow-up Pap tests (82%) than did those with self-test negative results (51%). No demographic differences were found in self-test return rate or HPV positivity. High acceptability was reported in participant surveys: most women (81%) had “mostly positive” overall thoughts about the self-test, and most reported being comfortable receiving the kit in the mail (99%), returning their self-collected sample by mail (82%), and receiving their test results by telephone (97%). Conclusions Conducting HPV self-testing through population-based recruitment, mailed kit delivery and return by mail, and results delivery by telephone has the potential to reach a broad segment of US underscreened women.
Abstract. Upper respiratory tract disease (URTD) caused by Mycoplasma agassizii has been hypothesized to contribute to the decline of some wild populations of gopher tortoises (Gopherus polyphemus). However, the force of infection (FOI) and the effect of URTD on survival in free-ranging tortoise populations remain unknown. Using four years (2003)(2004)(2005)(2006) of mark-recapture and epidemiological data collected from 10 populations of gopher tortoises in central Florida, USA, we estimated the FOI (probability per year of a susceptible tortoise becoming infected) and the effect of URTD (i.e., seropositivity to M. agassizii) on apparent survival rates. Sites with high (!25%) seroprevalence had substantially higher FOI (0.22 6 0.03; mean 6 SE) than low (,25%) seroprevalence sites (0.04 6 0.01). Our results provide the first quantitative evidence that the rate of transmission of M. agassizii is directly related to the seroprevalence of the population. Seropositive tortoises had higher apparent survival (0.99 6 0.0001) than seronegatives (0.88 6 0.03), possibly because seropositive tortoises represent individuals that survived the initial infection, developed chronic disease, and experienced lower mortality during the four-year span of our study. However, two lines of evidence suggested possible effects of mycoplasmal URTD on tortoise survival. First, one plausible model suggested that susceptible (seronegative) tortoises in high seroprevalence sites had lower apparent survival rates than did susceptible tortoises in low seroprevalence sites, indicating a possible acute effect of infection. Second, the number of dead tortoise remains detected during annual site surveys increased significantly with increasing site seroprevalence, from ;1 to ;5 shell remains per 100 individuals. If (as our results suggest) URTD in fact reduces adult survival, it could adversely influence the population dynamics and persistence of this latematuring, long-lived species.
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