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BackgroundRotavirus vaccine effectiveness is reduced among children in low-income countries. Indirect (transmission-mediated) effects of rotavirus vaccine might contribute to the total population effect of vaccination. We aimed to examine risk factors for transmission of rotavirus to household contacts in Blantyre, Malawi, and estimated the effectiveness of rotavirus vaccine in preventing transmission of infection to household contacts.MethodsIn this prospective household cohort study, we recruited children born after Sept 17, 2012, and aged at least 6 weeks (vaccine-eligible children) with acute rotavirus gastroenteritis and their household contacts, in four government health facilities in Blantyre, Malawi. Clinical data, a bulk stool sample, and 1-2 mL of serum were collected from case children at presentation. Clinical data and stool samples were also prospectively collected from household contacts over 14 days from presentation. A single stool sample was collected from control households containing asymptomatic children who were frequency age-matched to case children. Samples were tested for rotavirus using semi-quantitative real-time PCR and for anti-rotavirus IgA using a semi-quantitative sandwich ELISA. Risk factors for household transmission of rotavirus infection and clinical disease, including disease severity and faecal shedding density, were identified using mixed effects logistic regression. Vaccine effectiveness against transmission was estimated as 1 minus the ratio of secondary attack rates in vaccinated and counterfactual unvaccinated populations, using vaccine effectiveness estimates from the associated diarrhoeal surveillance platform to estimate the counterfactual secondary attack rate without vaccination.FindingsBetween Feb 16, 2015, and Nov 11, 2016, we recruited 196 case households (705 members) and 55 control households (153 members). Household secondary attack rate for rotavirus infection was high (434 [65%] of 665 individuals) and secondary attack rate for clinical disease was much lower (37 [5%] of 698). Asymptomatic infection in control households was common (40 [28%] of 144). Increasing disease severity in an index child (as measured by Vesikari score) was associated with increased risk of transmission of infection (odds ratio 1·17 [95% CI 1·06-1·30) and disease (1·28 [1·08-1·52]) to household contacts. Estimated vaccine effectiveness against transmission was 39% (95% CI 16-57).InterpretationRotavirus vaccine has the potential to substantially reduce household rotavirus transmission. This finding should be considered in clinical and health economic assessments of vaccine effectiveness.FundingWellcome Trust, US National Institutes of Health, and US National Institute of Allergy and Infectious Diseases.

Building on previous multicountry surveillance studies of typhoid and others salmonelloses such as the Diseases of the Most Impoverished program and the Typhoid Surveillance in Africa Project, several ongoing blood culture surveillance studies are generating important data about incidence, severity, transmission, and clinical features of invasive Salmonella infections in sub-Saharan Africa and South Asia. These studies are also characterizing drug resistance patterns in their respective study sites. Each study answers a different set of research questions and employs slightly different methodologies, and the geographies under surveillance differ in size, population density, physician practices, access to healthcare facilities, and access to microbiologically safe water and improved sanitation. These differences in part reflect the heterogeneity of the epidemiology of invasive salmonellosis globally, and thus enable generation of data that are useful to policymakers in decision-making for the introduction of typhoid conjugate vaccines (TCVs). Moreover, each study is evaluating the large-scale deployment of TCVs, and may ultimately be used to assess post-introduction vaccine impact. The data generated by these studies will also be used to refine global disease burden estimates. It is important to ensure that lessons learned from these studies not only inform vaccination policy, but also are incorporated into sustainable, low-cost, integrated vaccine-preventable disease surveillance systems.

A key question for infectious disease dynamics is the impact of the climate on future burden. Here, we evaluate the climate drivers of respiratory syncytial virus (RSV), an important determinant of disease in young children. We combine a dataset of county-level observations from the US with state-level observations from Mexico, spanning much of the global range of climatological conditions. Using a combination of nonlinear epidemic models with statistical techniques, we find consistent patterns of climate drivers at a continental scale explaining latitudinal differences in the dynamics and timing of local epidemics. Strikingly, estimated effects of precipitation and humidity on transmission mirror prior results for influenza. We couple our model with projections for future climate, to show that temperature-driven increases to humidity may lead to a northward shift in the dynamic patterns observed and that the likelihood of severe outbreaks of RSV hinges on projections for extreme rainfall.

Rotavirus vaccination has substantially reduced the incidence of rotavirus-associated gastroenteritis (RVGE) in high-income countries, but vaccine impact and estimated effectiveness are lower in low-income countries for reasons that are poorly understood. We used mathematical modeling to quantify rotavirus vaccine impact and investigate reduced vaccine effectiveness, particularly during the second year of life, in Malawi, where vaccination was introduced in October 2012 with doses at 6 and 10 weeks. We fitted models to 12 years of prevaccination data and validated the models against postvaccination data to evaluate the magnitude and duration of vaccine protection. The observed rollout of vaccination in Malawi was predicted to lead to a 26 to 77% decrease in the overall incidence of moderate-to-severe RVGE in 2016, depending on assumptions about waning of vaccine-induced immunity and heterogeneity in vaccine response. Vaccine effectiveness estimates were predicted to be higher among 4- to 11-month-olds than 12- to 23-month-olds, even when vaccine-induced immunity did not wane, due to differences in the rate at which vaccinated and unvaccinated individuals acquire immunity from natural infection. We found that vaccine effectiveness during the first and second years of life could potentially be improved by increasing the proportion of infants who respond to vaccination or by lowering the rotavirus transmission rate. An additional dose of rotavirus vaccine at 9 months of age was predicted to lead to higher estimated vaccine effectiveness but to only modest (5 to 16%) reductions in RVGE incidence over the first 3 years after introduction, regardless of assumptions about waning of vaccine-induced immunity.

Cohort studies, randomized trials, and post-licensure studies have reported reduced natural and vaccine-derived protection against rotavirus gastroenteritis (RVGE) in low- and middle-income countries. While susceptibility of children to rotavirus is known to vary within and between settings, implications for estimation of immune protection are not well understood. We sought to re-estimate naturally-acquired protection against rotavirus infection and RVGE, and to understand how differences in susceptibility among children impacted estimates. We re-analyzed data from studies conducted in Mexico City, Mexico and Vellore, India. Cumulatively, 573 rotavirus-unvaccinated children experienced 1418 rotavirus infections and 371 episodes of RVGE over 17,636 child-months. We developed a model that characterized susceptibility to rotavirus infection and RVGE among children, accounting for aspects of the natural history of rotavirus and differences in transmission rates between settings. We tested whether model-generated susceptibility measurements were associated with demographic and anthropometric factors, and with the severity of RVGE symptoms. We identified greater variation in susceptibility to rotavirus infection and RVGE in Vellore than in Mexico City. In both cohorts, susceptibility to rotavirus infection and RVGE were associated with male sex, lower birth weight, lower maternal education, and having fewer siblings; within Vellore, susceptibility was also associated with lower socioeconomic status. Children who were more susceptible to rotavirus also experienced higher rates of rotavirus-negative diarrhea, and higher risk of moderate-to-severe symptoms when experiencing RVGE. Simulations suggested that discrepant estimates of naturally-acquired immunity against RVGE can be attributed, in part, to between-setting differences in susceptibility of children, but result primarily from the interaction of transmission rates with age-dependent risk for infections to cause RVGE. We found that more children in Vellore than in Mexico City belong to a high-risk group for rotavirus infection and RVGE, and demonstrate that unmeasured individual- and age-dependent susceptibility may influence estimates of naturally-acquired immune protection against RVGE.

Significant variations have been observed in viral copies generated during SARS-CoV-2 infections. However, the factors that impact viral copies and infection dynamics are not fully understood, and may be inherently dependent upon different viral and host factors. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the impact of virus genetic variation on changes in viral copies adjusted for host age and vaccination status. Using a genome-wide association study (GWAS) approach, we identified multiple single-nucleotide polymorphisms (SNPs) corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. We further applied a marginal epistasis test to detect interactions among SNPs and identified multiple pairs of substitutions located in the spike gene that have non-linear effects on viral copies. We also analyzed the temporal patterns and found that SNPs associated with increased viral copies were predominantly observed in Delta and Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were only observed in infections with Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes that are worth further exploration. We argue that this approach can be used more broadly across pathogens to characterize emerging variants and monitor therapeutic interventions. Author summary: Our study explores why viral load (copies measured by RT-qPCR) varies during SARS-CoV-2 infections by analyzing viral mutations and measuring viral copies in 9,902 individuals over two years. We aimed to understand how genetic differences in SARS-CoV-2 influence viral copies, considering host age and vaccination status. Using a genome-wide association study (GWAS), we identified several single-nucleotide polymorphisms (SNPs) in the virus linked to variations in viral levels. Notably, interactions between certain SNPs in the spike gene had non-linear effects on viral copies. Our analysis revealed that SNPs associated with higher viral copies were common in Delta and Omicron BA.2/BA.4/BA.5/XBB variants, while those linked to lower levels were mainly found in Omicron BA.1. This research highlights GWAS as a powerful tool for exploring virus genetics and suggests it can be broadly applied to monitor new variants of COVID-19 and other infectious diseases. [ABSTRACT FROM AUTHOR]

BACKGROUND:Planning interventions to respond to cholera epidemics requires an understanding of the major transmission routes. Interrupting short-cycle (household, foodborne) transmission may require different approaches as compared long-cycle (environmentally-mediated/waterborne) transmission. However, differentiating the relative contribution of short- and long-cycle routes has remained difficult, and most cholera outbreak control efforts focus on interrupting long-cycle transmission. Here we use high-resolution epidemiological and municipal infrastructure data from a cholera outbreak in 1853 Copenhagen to explore the relative contribution of short- and long-cycle transmission routes during a major urban epidemic. METHODOLOGY/PRINCIPAL FINDINGS:We fit a spatially explicit time-series meta-population model to 6,552 physician-reported cholera cases from Copenhagen in 1853. We estimated the contribution of long-cycle waterborne transmission between neighborhoods using historical municipal water infrastructure data, fitting the force of infection from hydraulic flow, then comparing model performance. We found the epidemic was characterized by considerable transmission heterogeneity. Some neighborhoods acted as localized transmission hotspots, while other neighborhoods were less affected or important in driving the epidemic. We found little evidence to support long-cycle transmission between hydrologically-connected neighborhoods. Collectively, these findings suggest short-cycle transmission was significant. CONCLUSIONS/SIGNIFICANCE:Spatially targeted cholera interventions, such as reactive vaccination or sanitation/hygiene campaigns in hotspot neighborhoods, would likely have been more effective in this epidemic than control measures aimed at interrupting long-cycle transmission, such as improving municipal water quality. We recommend public health planners consider programs aimed at interrupting short-cycle transmission as essential tools in the cholera control arsenal.

Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

BackgroundObservational studies in socioeconomically distinct populations have yielded conflicting conclusions about the strength of naturally acquired immunity against rotavirus gastroenteritis (RVGE), mirroring vaccine underperformance in low-income countries. We revisited birth cohort studies to understand naturally acquired protection against rotavirus infection and RVGE.MethodsWe reanalyzed data from 200 Mexican and 373 Indian children followed from birth to 2 and 3 years of age, respectively. We reassessed protection against RVGE, decomposing the incidence rate into the rate of rotavirus infection and the risk of RVGE given infection, and tested for serum antibody correlates of protection using regression models.ResultsRisk for primary, secondary, and subsequent infections to cause RVGE decreased per log-month of age by 28% (95% confidence interval [CI], 12%-41%), 69% (95% CI, 30%-86%), and 64% (95% CI, -186% to 95%), respectively, in Mexico City, and by 10% (95% CI, -1% to 19%), 51% (95% CI, 41%-59%) and 67% (95% CI, 57%-75%), respectively, in Vellore. Elevated serum immunoglobulin A and immunoglobulin G titers were associated with partial protection against rotavirus infection. Associations between older age and reduced risk for RVGE or moderate-to-severe RVGE given infection persisted after controlling for antibody levels.ConclusionsDissimilar estimates of protection against RVGE may be due in part to age-related, antibody-independent risk for rotavirus infections to cause RVGE.

More than 5 years after a United Nations peacekeeping battalion introduced cholera to Haiti, over 150,000 peacekeepers continue to be deployed annually from countries where cholera is endemic. The United Nations has thus far declined to provide antimicrobial chemoprophylaxis to peacekeepers, a policy based largely on concerns that the risks of drug resistance generation and spread would outweigh the potential benefits of preventing future cholera importations. In this study, we sought to better understand the relative benefits and risks of cholera chemoprophylaxis for peacekeepers in terms of antibiotic resistance. Using a stochastic model to quantify the potential impact of chemoprophylaxis on importation and transmission of drug-resistant and drug-sensitive Vibrio cholerae, we found that chemoprophylaxis would decrease the probability of cholera importation but would increase the expected number of drug-resistant infections if an importation event were to occur. Despite this potential increase, we found that at least 10 drug-sensitive infections would likely be averted per excess drug-resistant infection under a wide range of assumptions about the underlying prevalence of drug resistance and risk of acquired resistance. Given these findings, policymakers should reconsider whether the potential resistance risks of providing antimicrobial chemoprophylaxis to peacekeepers are sufficient to outweigh the anticipated benefits.

BackgroundUpcoming vaccination efforts against typhoid fever require an assessment of the baseline burden of disease in countries at risk. There are no typhoid incidence data from most low- and middle-income countries (LMICs), so model-based estimates offer insights for decision-makers in the absence of readily available data.MethodsWe developed a mixed-effects model fit to data from 32 population-based studies of typhoid incidence in 22 locations in 14 countries. We tested the contribution of economic and environmental indices for predicting typhoid incidence using a stochastic search variable selection algorithm. We performed out-of-sample validation to assess the predictive performance of the model.ResultsWe estimated that 17.8 million cases of typhoid fever occur each year in LMICs (95% credible interval: 6.9-48.4 million). Central Africa was predicted to experience the highest incidence of typhoid, followed by select countries in Central, South, and Southeast Asia. Incidence typically peaked in the 2-4 year old age group. Models incorporating widely available economic and environmental indicators were found to describe incidence better than null models.ConclusionsRecent estimates of typhoid burden may under-estimate the number of cases and magnitude of uncertainty in typhoid incidence. Our analysis permits prediction of overall as well as age-specific incidence of typhoid fever in LMICs, and incorporates uncertainty around the model structure and estimates of the predictors. Future studies are needed to further validate and refine model predictions and better understand year-to-year variation in cases.

BackgroundMalaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region.MethodsThis study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models.ResultsTwo models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts.ConclusionResults indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.

BackgroundIntroduction of Vibrio cholerae to Haiti during the deployment of United Nations (UN) peacekeepers in 2010 resulted in one of the largest cholera epidemics of the modern era. Following the outbreak, a UN-commissioned independent panel recommended three pre-deployment intervention strategies to minimize the risk of cholera introduction in future peacekeeping operations: screening for V. cholerae carriage, administering prophylactic antimicrobial chemotherapies, or immunizing with oral cholera vaccines. However, uncertainty regarding the effectiveness of these approaches has forestalled their implementation by the UN. We assessed how the interventions would have impacted the likelihood of the Haiti cholera epidemic.Methods and findingsWe developed a stochastic model for cholera importation and transmission, fitted to reported cases during the first weeks of the 2010 outbreak in Haiti. Using this model, we estimated that diagnostic screening reduces the probability of cases occurring by 82% (95% credible interval: 75%, 85%); however, false-positive test outcomes may hamper this approach. Antimicrobial chemoprophylaxis at time of departure and oral cholera vaccination reduce the probability of cases by 50% (41%, 57%) and by up to 61% (58%, 63%), respectively. Chemoprophylaxis beginning 1 wk before departure confers a 91% (78%, 96%) reduction independently, and up to a 98% reduction (94%, 99%) if coupled with vaccination. These results are not sensitive to assumptions about the background cholera incidence rate in the endemic troop-sending country. Further research is needed to (1) validate the sensitivity and specificity of rapid test approaches for detecting asymptomatic carriage, (2) compare prophylactic efficacy across antimicrobial regimens, and (3) quantify the impact of oral cholera vaccine on transmission from asymptomatic carriers.ConclusionsScreening, chemoprophylaxis, and vaccination are all effective strategies to prevent cholera introduction during large-scale personnel deployments such as that precipitating the 2010 Haiti outbreak. Antimicrobial chemoprophylaxis was estimated to provide the greatest protection at the lowest cost among the approaches recently evaluated by the UN.

Background: When a randomized controlled trial fails to demonstrate statistically significant efficacy against the primary endpoint, a potentially costly new trial would need to be conducted to receive licensure. Incorporating data from previous trials might allow for more efficient follow-up trials to demonstrate efficacy, speeding the availability of effective vaccines. Methods: Based on the outcomes from a failed trial of a maternal vaccine against respiratory syncytial virus (RSV), we simulated data for a new Bayesian group-sequential trial. We analyzed the data either ignoring data from the previous trial (i.e., weakly informative prior distributions) or using prior distributions incorporating the historical data into the analysis. We evaluated scenarios where efficacy in the new trial was the same, greater than, or less than that in the original trial. For each scenario, we evaluated the statistical power and type I error rate for estimating the vaccine effect following interim analyses. Results: When we used a stringent threshold to control the type I error rate, analyses incorporating historical data had a small advantage over trials that did not. If control of type I error is less important (e.g., in a postlicensure evaluation), the incorporation of historical data can provide a substantial boost in efficiency. Conclusions: Due to the need to control the type I error rate in trials used to license a vaccine, incorporating historical data provides little additional benefit in terms of stopping the trial early. However, these statistical approaches could be promising in evaluations that use realworld evidence following licensure. [ABSTRACT FROM AUTHOR]

Background: With more than 1.2 million illnesses and 29,000 deaths in sub-Saharan Africa in 2017, typhoid fever continues to be a major public health problem. Effective control of the disease would benefit from an understanding of the subnational geospatial distribution of the disease incidence. Method: We collated records of the incidence rate of typhoid fever confirmed by culture of blood in Africa from 2000 to 2022. We estimated the typhoid incidence rate for sub-Saharan Africa on 20 km × 20 km grids by exploring the association with geospatial covariates representing access to improved water and sanitation, health conditions of the population, and environmental conditions. Results: We identified six published articles and one pre-print representing incidence rate estimates in 22 sites in 2000–2022. Estimated incidence rates showed geospatial variation at sub-national, national, and regional levels. The incidence rate was high in Western and Eastern African subregions followed by Southern and Middle African subregions. By age, the incidence rate was highest among 5–14 yo followed by 2–4 yo, > 14 yo, and 0–1 yo. When aggregated across all age classes and grids that comprise each country, predicted incidence rates ranged from 43.7 (95% confidence interval: 0.6 to 591.2) in Zimbabwe to 2,957.8 (95% CI: 20.8 to 4,245.2) in South Sudan per 100,000 person-years. Sub-national heterogeneity was evident with the coefficient of variation at the 20 km × 20 km grid-level ranging from 0.7 to 3.3 and was generally lower in high-incidence countries and widely varying in low-incidence countries. Conclusion: Our study provides estimates of 20 km × 20 km incidence rate of typhoid fever across sub-Saharan Africa based on data collected from 2000 through 2020. Increased understanding of the subnational geospatial variation of typhoid fever in Africa may inform more effective intervention programs by better targeting resources to heterogeneously disturbed disease risk. Author summary: Typhoid fever remains a significant health challenge in low- and middle-income nations, especially in sub-Saharan Africa. A comprehensive understanding of the disease's geospatial distribution is pivotal for its control—a gap previous studies overlooked. Addressing this, we undertook a study to chart the incidence of typhoid fever throughout sub-Saharan Africa. Using data from 2000 to 2022, we developed high-resolution maps with a granularity of 20 km by 20 km, detailing the spatial distribution of typhoid incidence. Our findings reveal pronounced disparities in typhoid incidence across different geospatial tiers: from local communities to entire nations and regions. Particularly, Western and Eastern Africa registered the highest incidences, with children aged 5–14 years being the most vulnerable. Distinctively, countries such as South Sudan reported alarmingly high figures, whereas Zimbabwe had notably fewer cases. Such insights are indispensable for health policymakers at local, national, and global levels. Pinpointing the areas hardest hit by typhoid allows for a more strategic allocation of resources and interventions. Armed with this data, we're better positioned to fight typhoid effectively and safeguard lives in sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Background: To meet regulatory approval, interventions must demonstrate efficacy against a primary outcome in randomized clinical trials. However, when there are multiple clinically relevant outcomes, selecting a single primary outcome is challenging. Incorporating data from multiple outcomes may increase statistical power in clinical trials. We examined methods for analyzing data on multiple endpoints, inspired by real-world trials of interventions against respiratory syncytial virus (RSV). Method: We developed a novel permutation test representing a weighted average of individual outcome test statistics (wavP) to evaluate intervention efficacy in a multiple endpoint analysis. We compared the power and type I error rate of this approach to the Bonferroni correction (bonfT) and the minP permutation test. We evaluated the different approaches using simulated data from three hypothetical trials varying the intervention efficacy, correlation, and incidence of the outcomes, and data from a real-world RSV clinical trial. Results: When the vaccine efficacy against different outcomes was similar, wavP yielded higher power than bonfT and minP ; in some scenarios the improvement in power was substantial. In settings where vaccine efficacy was notably larger against one endpoint compared with the others, all three methods had similar power. We developed an R package, PERmutation basEd ANalysis of mulTiple Endpoints (PERMEATE), to guide the selection of the most appropriate method for analyzing multiple endpoints in clinical trials. Conclusions: Analyzing multiple endpoints using a weighted permutation method can increase power, whereas controlling the type I error rate compared with established methods under conditions mirroring real-world RSV clinical trials. [ABSTRACT FROM AUTHOR]

We initiated a nationwide prospective study to monitor respiratory syncytial virus (RSV)–related pediatric hospitalizations in 46 hospitals throughout the Netherlands between May 2021 and August 2022. We showed year-round RSV transmission in the Netherlands after an initial 2021 summer outbreak. The pattern was unprecedented and distinct from neighboring countries. We extended a dynamic simulation model to evaluate the impact of waning immunity on pediatric RSV hospitalizations in the Netherlands using 4 different scenarios. Our results suggest that the observed continuous RSV transmission pattern could be associated with waning immunity due to the period of very low RSV circulation during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]