The simulations examined how the timing and extent of infection-acquired immunity could affect the apparent performance of Shigella vaccines. In high-incidence settings, repeated exposure may allow unvaccinated infants to accumulate natural immunity, potentially bringing their immune status closer to that of vaccinated infants. A trial conducted after this convergence could therefore record a lower vaccine efficacy than the vaccine would achieve in a fully immunologically naïve population. The magnitude of the effect depended on the trial design and on assumptions about the natural history of Shigella, including how quickly immunity develops and how long it persists.

Researchers modeled trials in settings with low, medium and high disease burdens. For each setting, they evaluated six combinations of surveillance and statistical analysis: active surveillance for Shigella infection or symptom-based reporting, each paired with a single-outcome model, a stratified recurrent-outcome model or a crude recurrent-outcome Cox proportional hazards model. The analysis measured bias in vaccine-efficacy estimates, the coverage of nominal 95% confidence intervals and the false-negative rate. Active infection surveillance with a single-outcome model was the only approach that remained unbiased throughout the scenarios tested. Among the other five approaches, the single-outcome model paired with symptom-based reporting performed least poorly.

Bias generally increased in higher-burden settings, where the accumulation of natural immunity was expected to be more pronounced. The results for realistically sized trials were also less favorable at higher-burden sites: confidence-interval coverage was worse, and the false-negative rate was higher. These findings identify a specific measurement challenge for late-stage Shigella vaccine trials rather than evidence that the vaccines themselves are ineffective. They also do not establish the size of the discrepancy in an actual trial, because the estimates are conditional on simulated inputs and limited published information about Shigella immunity and natural history. The study’s conclusion is that observed efficacy is likely to understate true efficacy in some circumstances, while careful design is needed to reduce that bias.

Subject of Research: Simulation analysis of how natural immunity and trial design affect estimates of Shigella vaccine efficacy

Article Title: Analysis of the impact of naturally-acquired immunity on Shigella vaccine performance to inform clinical trials: A simulation-based modeling study

Article References: Amin, A. B., Garcia Quesada, M., Trudell, D., Dean, N. E., Lopman, B. A., Platts-Mills, J. A., & Rogawski McQuade, E. T. (2026). Analysis of the impact of naturally-acquired immunity on Shigella vaccine performance to inform clinical trials: A simulation-based modeling study. PLOS Medicine, 23(10), e1004878. https://doi.org/10.1371/journal.pmed.1004878

Image Credits: AI Generated

DOI: 10.1371/journal.pmed.1004878

Keywords: Shigella, vaccine efficacy, natural immunity, clinical trials, epidemiology, simulation modeling, active surveillance, diarrheal disease, statistical bias, Analysis, impact, naturally-acquired

The pilot was designed to test a high-frequency symptom-reporting approach that could later be combined with the Chitwan Valley Family Study, a longitudinal household and community panel that has collected detailed information about children, parents, households, and communities since 1996. Researchers randomly selected households with children under five from within the family study’s geographic area but outside its established sample neighborhoods, avoiding contamination of the samples planned for the follow-on investigation. Sampling was stratified by the number of age-eligible children, with about half of the households having one child under five and about half having two. Half of the households were then randomized to receive a daily text-message reminder, with this randomization also stratified by the number of eligible children.

All respondents were mothers of children under five. Trained interviewers visited the selected households, confirmed that the children met the age requirement, obtained informed consent, and explained the symptom definitions using the diary’s written instructions and pictures. Diarrhea, for example, was defined as three or more loose stools in a 24-hour period. Each paper diary contained seven daily checklists for recording diarrhea, fever, cough, runny nose, fast or labored breathing, loss of appetite, and fatigue. The paper format was intended to make the daily observations easier for parents to record without requiring a visit or telephone contact for every day of the study period.

During the 12-week study, a trained interviewer called each participating mother every week. The interview was designed to take less than 10 minutes and used a computer-assisted personal-interview procedure. Interviewers asked which symptoms the children had experienced and on which days they had occurred. When a respondent had not recorded symptoms in the diary, the interview provided an opportunity to report them from memory. Interviewers also recorded whether the information had come from the completed checklist, recall, or a combination of both, making it possible to distinguish information documented at the time from information supplied later. The final weekly interview included questions about respondents’ experiences with the study.

A diary week was classified as complete only when all days contained complete data for all enrolled children in the household. The participants’ children averaged 26.9 months of age, with a standard deviation of 15.5 months, and 51.8% were female. The proportion of fully completed diary weeks ranged from 87.5% to 94.6% across the study weeks, apart from the first and last weeks, when completion was 67.9% and 80.3%, respectively. The study therefore recorded lower full-week completion at both ends of the observation period, although the results do not identify a cause for those differences.

Mixed-effects logistic regression was used to assess how diary completion varied by week while accounting for clustering at the respondent, or mother, level. The unadjusted model evaluated completion by collection week. A fuller model additionally accounted for collection week, child sex, child age in years, and whether the mother had one or two children enrolled in the study. The investigators reported odds ratios with 95% confidence intervals and p-values. They also used cumulative incidence curves and kernel-density plots to estimate the incidence and prevalence of reported symptoms, and summarized the qualitative feedback collected at the end of the study.

Daily text reminders did not show a statistically significant association with completion. Mothers who received reminders completed 86.3% of diaries fully, compared with 91.3% among those who did not receive texts. The regression estimated the odds of completion at 1.19 for households receiving reminders, but the 95% confidence interval was wide, from 0.31 to 4.53, indicating substantial uncertainty. The pilot therefore did not establish a benefit or disadvantage associated with receiving reminders. It also did not demonstrate that the messages changed the number or type of symptoms reported. Nevertheless, all respondents who had received a text described it as helpful, while 73.7% of those who had not received one said they would prefer to have it.

Runny nose and cough had the highest reported incidence and overall prevalence, whereas fatigue and difficulty breathing were reported least often. The investigators said the pattern of symptom frequency was consistent with their expectations for the season in which data were collected. They also suggested that more common symptoms being reported more often indicated that respondents had understood the study definitions. These observations concern what parents recorded during a single collection period; they do not establish a geographic contrast or demonstrate a change in childhood illness over time. The pilot did not use a diagnostic instrument or clinical or laboratory confirmation to evaluate whether individual entries represented infectious disease.

Respondents said that both the text messages and storing the diary in a visible place helped them remember to complete it each day. They requested a smaller diary and a format that would be easier to store and clearer to complete. The pilot therefore informed several changes for the larger study within the Chitwan Valley Family Study: advising participants about possible storage locations, redesigning the diary, and modifying the protocol so that household caregivers other than the enrolled mother could help complete the written records. Although the pilot found no clear effect of reminders on completion, the favorable feedback led the team to offer daily text messages to all participants in the larger study.

The results support daily parent-reported symptom diaries as a potentially practical way to measure acute childhood illness, but several limitations constrain how broadly the findings can be generalized. The sample included only 40 households and 56 children, and symptom reporting covered 12 weeks, compared with 52 weeks in the larger planned study. The children came from one geographic area and may not represent the wider pediatric population of Chitwan or the full family-study sample. Seasonality also influenced the illnesses reported during the collection period. Longer participation could increase attrition, while selection effects and social desirability might affect diary completion or the information parents provide. The authors proposed cross-checking diaries against respondent-reported data in the follow-on study as one way to identify possible discrepancies.

Within those bounds, the pilot provides evidence that parents are willing to record daily symptoms and that the written diaries can be completed at high rates over a 12-week period. A daily record preserves the timing and frequency of respiratory and diarrheal symptoms, while the brief weekly interview provides a structured opportunity to fill gaps through recall and documents how each report was obtained. When combined with existing social, demographic, household, and community information from the Chitwan Valley Family Study, these data could support analysis of the contextual factors associated with acute illness in early childhood. The study did not demonstrate clinical benefits, improved child health outcomes, or the diagnostic accuracy of the diaries. Its immediate contribution was to identify a workable, relatively low-cost data-collection strategy and refine it for a larger study in Nepal, with possible application in other low- and middle-income countries.

Subject of Research: Feasibility of daily parent-reported respiratory and diarrheal symptom diaries for children under five in Nepal

Article Title: Feasibility of high frequency parent-reported respiratory and diarrheal symptom data for children under five in a pilot study cohort

Article References: Dwan, M., Chaudhary, I., Kubale, J., Ghimire, R., Noppert, G., Ghimire, D., & Treleaven, E. (2026). Feasibility of high frequency parent-reported respiratory and diarrheal symptom data for children under five in a pilot study cohort. Public Health in Practice, 12, Article 100869. https://doi.org/10.1016/j.puhip.2026.100869

Image Credits: AI Generated

DOI: 10.1016/j.puhip.2026.100869

Keywords: childhood illness, symptom diaries, parent reporting, Nepal, Chitwan Valley, respiratory symptoms, diarrheal disease, longitudinal research, public health, low-income settings, Feasibility, high

The investigation identified a total of 237 cases of acute diarrheal illness during the outbreak period. The age distribution of cases was striking: more than half of those affected, 55.2 percent, were individuals under 20 years of age. This pattern is consistent with the epidemiology of many enteric infections, where younger people, with less developed hygiene habits, closer contact in household and school settings, and greater susceptibility, often bear a disproportionate share of the disease burden. The concentration of cases among children and adolescents also raises concerns about the potential for onward transmission within households and community institutions, a dynamic that the investigators would go on to examine through the lens of spatial statistics.

Environmental investigations formed a central pillar of the outbreak response. The team sampled water sources across the affected area, including the municipal supply maintained by the Public Health Engineering Department and household-level storage containers. The results were revealing: microbiological contamination was detected in household-stored drinking water and in a household well, whereas no contamination was found in the sampled PHED water supply source. This dissociation between a clean central supply and contaminated point-of-use water is a well-recognized hazard in rural water systems, where water that leaves a treatment facility in good condition can be recontaminated during storage and handling in the home. Taken together with the observed clustering of cases, the findings suggest that localized environmental exposure, potentially associated with point-of-use water contamination, played a role in the outbreak.

The microbiological picture that emerged from patient samples was more complex than a single-organism explanation would allow. Stool samples from 22 patients were tested, and Norovirus GII was identified in 22.7 percent of them. Blood samples from 18 patients were screened for viral hepatitis, and Hepatitis A virus was detected in 5.6 percent of those samples. Escherichia coli was detected in all 16 stool samples that underwent microbiological analysis, although the authors caution that these organisms were probably normal gut flora and that the samples were not further screened for specific diarrheagenic strains; at the same time, they note that the possibility of pathogenic E. coli strains contributing to illness cannot be completely ruled out. This multi-pathogen etiology complicates the interpretation of the outbreak but is not unusual in settings where water, sanitation, and hygiene infrastructure is strained and multiple enteric pathogens can circulate simultaneously.

The detection of Norovirus GII is particularly noteworthy. Noroviruses are a leading cause of acute gastroenteritis worldwide, responsible for explosive outbreaks in settings ranging from cruise ships to schools, and the GII genogroup contains the strains most commonly associated with human disease. Yet in rural Bihar, diarrheal outbreaks have traditionally been attributed to bacterial pathogens, particularly Vibrio cholerae and various enteric bacteria, and viral etiologies have often gone undetected simply because diagnostic capacity for them has been limited. The identification of Norovirus GII in more than a fifth of tested patients suggests that the etiological profile of diarrheal disease in the region may be evolving, or at least that improved molecular diagnostics are revealing pathogens that earlier investigations would have missed. Either way, the finding underscores the importance of maintaining and expanding viral diagnostic capacity, such as that provided by the Viral Research and Diagnostic Laboratory network, in state surveillance systems.

What sets this investigation apart methodologically is its use of geostatistical analysis to characterize the spatial structure of transmission. The researchers began by applying Global Moran’s I statistics to the geographic coordinates of cases, a test that asks whether the spatial distribution of disease intensity deviates from complete spatial randomness. The answer was a clear yes: the analysis confirmed significant global spatial clustering, with a Moran’s I value of 0.1161, a z-score of 3.64, and a p-value below 0.001. In practical terms, this means that cases were not scattered randomly across the landscape but tended to occur near other cases, a pattern consistent with a localized environmental exposure or with person-to-person transmission operating at the neighborhood scale.

Global statistics, however, can only say that clustering exists somewhere in the study area; they cannot say where. To pinpoint the locations of intense transmission, the team turned to the Getis-Ord Gi* statistic, a local indicator of spatial association that evaluates each location against its neighbors and assigns a measure of statistical confidence to the degree of clustering. Combined with Inverse Distance Weighting, a technique that interpolates disease intensity across the map based on nearby observations, the Getis-Ord Gi* analysis identified high-intensity clusters at 99 percent confidence, corresponding to the highest bin in the classification scheme, specifically within the Paswan and Manjhi Tolas. These are settlements of marginalized Mahadalit communities, and their identification as hot spots directs attention to the intersections of social vulnerability, environmental exposure, and infectious disease risk that shape outbreak patterns in the region.

The spatial findings, interpreted alongside the microbiological and environmental evidence, led the investigators to a nuanced conclusion about the outbreak’s dynamics. Rather than a single confirmed point source, such as one contaminated well or one contaminated batch of water, the pattern of statistically significant clustering within specific settlements, combined with contamination found at the household level rather than in the central supply, supports a hypothesis of environmental exposure followed by subsequent person-to-person transmission. This kind of mixed dynamic is common in norovirus outbreaks, where an initial environmental introduction can seed chains of transmission that spread efficiently through close contact, contaminated surfaces, and the characteristic aerosolization that accompanies vomiting. Recognizing such dynamics matters operationally, because interrupting person-to-person transmission requires interventions, including hygiene promotion, isolation of cases, and disinfection, that go beyond fixing a single water source.

Beyond its findings about this particular outbreak, the study offers a replicable template for outbreak investigation in settings where surveillance data are often aggregated at coarse administrative levels, obscuring the fine-grained spatial structure of transmission. By applying localized spatial autocorrelation to case-level coordinates, the team transformed routine surveillance data into precise, statistically robust maps of disease clustering. The authors argue that integrating such advanced spatial statistics into routine outbreak investigations enhances the precision of public health interventions, allowing resources to be targeted to the specific neighborhoods and communities where transmission is most intense. In a state like Bihar, where diarrheal disease outbreaks remain a persistent public health challenge and where marginalized communities such as the Mahadalit tolas face compounding environmental and social risks, this approach promises a more objective and equitable basis for response.

The investigation was conducted as a government-mandated public health response, exempted from individual ethics review under the ICMR National Ethical Guidelines as fundamental public health practice, and authorized by the Office of the District Magistrate of Jehanabad. It drew on the coordinated efforts of district surveillance units, rapid response teams, block health officials, and community health workers, supported technically by the Asian Development Research Institute and health system strengthening funding from the Gates Foundation. As molecular diagnostics become more widely available and spatial analytical tools become more accessible to district-level teams, the Bihar experience suggests that the future of outbreak response in resource-constrained settings may lie in combining these approaches: identifying not only what pathogen is making people sick, but precisely where transmission is concentrated, and tailoring interventions to the social and environmental realities of the communities most affected.

Subject of Research: Geostatistical analysis of a norovirus GII-associated acute diarrheal outbreak in Jehanabad, Bihar, India

Article Title: Spatiotemporal dynamics and multi-pathogen etiology of a norovirus GII-associated diarrheal outbreak in Bihar: a geostatistical analysis of localized spatial autocorrelation

Article References: Kumar, A., Gupta, N., Mishra, R., Sharma, A., Razdan, D., Kumar, A., Rai, A., Pandey, A., Prasad, D., Mishra, R., & Mahapatra, S. (2026). Spatiotemporal dynamics and multi-pathogen etiology of a norovirus GII-associated diarrheal outbreak in Bihar: a geostatistical analysis of localized spatial autocorrelation. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14497-8

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14497-8

Keywords: Norovirus GII, spatial autocorrelation, Getis-Ord Gi*, Moran's I, outbreak investigation, Bihar, diarrheal disease, Hepatitis A virus, water contamination, epidemiology, geostatistics, public health

The study, published in Environmental Advances, drew on electronic health records from the Medical Research Council Unit The Gambia clinic in Keneba, a facility that has provided free healthcare to residents of the surrounding West Kiang region for decades. Between January 2010 and December 2022, the clinic recorded 11,331 visits for diarrheal diseases and 29,420 visits for skin infections. Roughly seven in ten diarrheal visits involved children under five, while skin infections were more evenly distributed across age groups. The researchers aggregated these visits into weekly counts and matched them against weekly rainfall and temperature data from the European Centre for Medium-Range Weather Forecasts ERA5-Land reanalysis dataset, extracted at roughly ten kilometre resolution for the grid cell containing the clinic.

Because the relationship between weather and disease is rarely linear, the team employed distributed lag non-linear models, a statistical framework that can capture both curved exposure-response relationships and effects that unfold over time. Weekly counts of clinic visits were highly overdispersed, so negative binomial regression was used, with natural cubic splines of time flexibly adjusting for long-term trends and seasonality. The models allowed rainfall effects to emerge across a zero-to-three-week lag window, chosen to encompass the incubation periods of the major pathogens involved as well as the time needed for environmental exposure, pathogen replication and the decision to seek care.

The headline finding is a threshold effect. For diarrheal disease, the cumulative risk of a clinic visit rose steadily as weekly rainfall increased, peaking somewhere between 35 and 40 millimetres of rain per week, after which the risk plateaued and drifted back toward null. A week with 20 millimetres of rainfall, roughly the 75th percentile of the full series, was associated with a 20 percent increase in diarrheal visits compared with dry weeks, after adjusting for temperature. Without that temperature adjustment, the apparent risk was 41 percent higher, a difference that proved to be one of the study’s most methodologically important observations.

Skin infections told a similar but not identical story. Risk climbed with rainfall up to a threshold of about 30 millimetres per week, then declined at heavier totals. Twenty millimetres of weekly rainfall was associated with a 39 percent increase in skin infection visits once temperature was accounted for, and the effect persisted across lags of one, two and three weeks, longer than the one-to-two-week window over which diarrheal risks appeared. The researchers suggest this may reflect different underlying mechanisms: diarrheal pathogens are typically ingested after relatively rapid contamination of water sources, while skin infections may follow slower routes of environmental exposure, crowding during wet weather and changes in hygiene practices when water becomes scarce or contaminated.

Stratifying the data by pathogen category revealed a striking asymmetry. Bacterial diarrheal visits carried the strongest rainfall association, with a 66 percent increase in risk at 20 millimetres of weekly rainfall after temperature adjustment, whereas viral diarrheal visits showed no clear evidence of a rainfall effect at all. A parallel pattern emerged for skin disease: bacterial skin infections were the most rainfall-sensitive category, though fungal and clinically classified local skin infections also showed elevated risks. This aligns with a growing body of evidence from other settings that rainfall and temperature shape the transmission of bacterial and viral enteric pathogens in fundamentally different ways, with wetter conditions generally favouring bacterial spread.

Age modified the risks in unexpected directions. For diarrheal disease, the rainfall association was stronger among patients aged five and over, with a 63 percent increase in risk at 20 millimetres of weekly rainfall, than among children under five, for whom no significant association was detected after temperature adjustment. The authors note that the vast majority of under-five diarrheal visits were classified as viral, which may partly explain the difference. For skin infections the pattern reversed: children under five bore the greater rainfall-associated burden, with a 77 percent increase in visits at 20 millimetres of rain, consistent with the idea that young children crawling and playing in contaminated standing water face heightened exposure. Sex-stratified analyses suggested slightly higher risks among females for both outcomes, though the evidence for modification by sex was weaker than for age.

Perhaps the most counterintuitive result concerns heavy rainfall events, defined as days receiving more than 21.05 millimetres of rain, the 95th percentile of rainy days between 2000 and 2022. In unadjusted models, weeks containing at least one such event were associated with substantially increased risks of both diarrheal and skin infection visits. But once maximum temperature was included in the models, those associations vanished entirely. And when total weekly rainfall was additionally controlled for, a heavy rainfall event was actually associated with a modest decrease in diarrheal risk. The authors propose that competing mechanisms may be at work: heavy rain can flush and dilute pathogens in water sources, while also improving water availability for hygiene, offsetting the contamination and infrastructure damage such events can cause.

The confounding role of temperature deserves emphasis, because many prior studies of rainfall and diarrheal disease have not adjusted for it at all. In The Gambia, temperature and rainfall are strongly inversely related, with the hottest weeks falling just before the onset of the rainy season. Failing to account for this coupling can therefore inflate or distort apparent rainfall effects. The sensitivity analyses were reassuring on other fronts: results held up under alternative methods of seasonal adjustment, different spline configurations, shorter and longer lag windows, and explicit adjustment for the sharp decline in diarrheal visits after rotavirus vaccine introduction in 2014. Crucially, rainfall showed no comparable association with clinic visits for routine child health checks, toothache or hypertension, outcomes that lie outside any plausible rainfall-transmission pathway, suggesting the findings are not simply an artefact of weather-driven changes in health-seeking behaviour.

The study has limitations the authors acknowledge. Clinic visits are a proxy for disease incidence rather than a direct measure, pathogen classifications rest on clinical assessment rather than laboratory confirmation, and reanalysis weather data averaged over ten-kilometre grid cells may smooth out the local extremes of rainfall that matter most. Even so, the work offers one of the most detailed pictures to date of how rainfall shapes water-related disease in West Africa, a region where such evidence has been sparse and where climate projections point toward greater rainfall variability and more intense wet-season events. As the authors conclude, the non-linear risks they document, together with the anticipated shifts in West African rainfall, argue for strengthening the climate resilience of water, sanitation and hygiene services, and for studying rainfall and temperature jointly rather than in isolation if early-warning systems for climate-sensitive diseases are to become a reality.

Subject of Research: The association between weekly rainfall, temperature and clinic visits for diarrheal diseases and skin infections in rural Gambia

Article Title: The impact of weekly rainfall on water-related diseases in The Gambia: a time-series analysis of health facility data

Article References: Bose, I., Part, C., Moirano, G., Murray, K. A., Green, R., Cerami, C., Mistry, M. N., & Kovats, S. (2026). The impact of weekly rainfall on water-related diseases in The Gambia: a time-series analysis of health facility data. Environmental Advances, 26, Article 100757. https://doi.org/10.1016/j.envadv.2026.100757

Image Credits: AI Generated

DOI: 10.1016/j.envadv.2026.100757

Keywords: rainfall, diarrheal disease, skin infections, The Gambia, time-series analysis, climate and health, heavy rainfall events, distributed lag non-linear models, water-related diseases, WASH, temperature confounding, West Africa