Infectious Diseases of Poverty

Brazil has one of the highest dengue burdens globally, with transmission influenced by climate events. Yet, the effects of compound climate extremes on dengue risk and prediction have not been quantified to date. Using a Bayesian spatiotemporal model of monthly dengue cases across 435 health regions from 2010 to 2025, we estimated relative risk associated with interacting long-lag and short-lag drought indicators and temperature anomalies across nine Koppen-Geiger climatic zones, adjusting for absolute temperature and El Nino-Southern Oscillation. Long-lag dry, mid-lag warm and short-lag wet conditions were associated with the highest relative risk in five climatic zones, with temperature anomalies modifying hydrometeorological dynamics more strongly in temperate than tropical areas. Climate covariates improved the prediction of case counts and outbreaks compared to baseline models at lead times of 1, 3, 6 and 12 months, and for the upcoming season 5 months ahead. Improvements were greatest in the Northeast, Southeast, and Midwest. Recent dengue incidence provided the greatest improvement at the 1-month lead, whereas combining incidence with climate information performed best at 3- and 6-month leads. We extended our framework to weekly state-level predictions of the season ahead to align with national public health planning. We proposed a multi-staged dengue forecasting approach to enhance early warning and response across Brazil.

Since its inception in 2003, the United States President's Emergency Plan for AIDS Relief (PEPFAR) has played a central role in HIV/AIDS prevention and treatment across Sub-Saharan Africa. Following the January 2025 suspension of United States foreign aid, which includes PEPFAR funding, countries across Sub-Saharan Africa demonstrated varying governmental responses to the resulting HIV funding disruptions. This study evaluates whether national characteristics were associated with a country's ability to respond to this funding crisis. Countries in Sub-Saharan Africa receiving PEPFAR funding were classified into one of three response categories: Level 1 (minimal or no governmental response), Level 2 (government response without sufficient plans or resources to fully offset funding losses), or Level 3 (high governmental response with strategies to maintain HIV/AIDS prevention and treatment services). Response categories were compared with national Human Development Index (HDI), GDP per capita, HIV prevalence, total population living with HIV, annual HIV mortality, and historical PEPFAR funding. Univariable proportional-odds ordinal logistic regression was used to identify factors associated with response level. Five countries (17.2%) were classified as Level 1, 10 (34.5%) as Level 2, and 14 (48.3%) as Level 3. Higher HDI was significantly associated with stronger governmental response (OR = 4.05; 95% CI, 1.49-11.04; Holm-adjusted p = 0.0376). GDP per capita (OR = 2.35; 95% CI, 1.00-5.51; unadjusted p = 0.0489) and HIV prevalence (OR = 3.53; 95% CI, 1.03-12.11; unadjusted p = 0.0452) demonstrated positive associations before adjustment for multiple comparisons, but neither remained significant after Holm correction (adjusted p = 0.2261 for both). Historical PEPFAR funding, total population living with HIV, and annual HIV mortality were not significantly associated with response level after adjustment. Countries with higher levels of human development demonstrated stronger governmental responses to the 2025 PEPFAR funding disruptions. Several countries with minimal documented responses were also affected by active conflict or political instability, potentially compounding their vulnerability to treatment interruptions. These findings suggest that broader national development may play an important role in governmental responses to funding disruptions and highlight the need to strengthen resilient health systems, diversify HIV financing, and prioritize support for countries at greatest risk of future funding shocks.

Importance: Coccidioidomycosis, also known as Valley fever, is a serious fungal disease caused by inhaling Coccidioides spores aerosolized from the soil. Despite rising public health concern, the distribution and incidence of coccidioidomycosis in the US remain poorly characterized as not all states are required to report cases, and case under-ascertainment is presumed to be high, particularly outside of the endemic region. Objective: To estimate monthly, county-level coccidioidomycosis incidence across the US while accounting for widespread under-ascertainment. Design, Setting, and Participants: We integrated multisource data, including human cases diagnosed in electronic health records, serological testing of dogs, and ecological and sociodemographic predictors, in a machine learning model estimating monthly, county-level coccidioidomycosis incidence. The model was trained on surveillance data from Arizona and California from 2013 to 2023, then applied to predict incidence in states across the contiguous US over the same time period. Main Outcomes and Measures: Incidence of coccidioidomycosis at the monthly county level. Results: The model predicted coccidioidomycosis incidence from 2013 to 2023 for 3,108 counties from all states in the contiguous US. The model identified 60 counties in non-reporting states where predicted incidence was [≥]2 cases per 100,000 population (considered moderate to high incidence). In states with mandatory reporting outside of Arizona and California, the model predicted county-level incidence rates that were 28% higher (95% bootstrap interval, 0.1%-69.8%) than those captured in national surveillance, equating to a total of 608 potentially missed cases per year (95% bootstrap interval, 340-964). Conclusions and Relevance: In this cross-sectional study, the model quantified case under-ascertainment for coccidioidomycosis relative to Arizona and California, and highlighted the potential for alternative data sources to fill in gaps in mandatory reporting. Estimating incidence while accounting for under-ascertainment and non-reporting may help efforts to improve public and physician awareness and to detect emergence in new regions.

Wolbachia-based interventions were less effective in achieving introgression in Rio de Janeiro than other settings. Reduced introgression occurred in locations where dengue was historically high, raising concerns of inequity. We examined factors affecting Wolbachia introgression in Rio through trajectory modeling, spatiotemporal Bayesian models, and Ae. aegypti abundance estimation. During the intervention (2017-2020), Wolbachia introgression was 26% (median; IQR,14-44%), with four distinct trajectories. Despite receiving more releases, densely populated areas with low socioeconomic status had lower introgression. In spatiotemporally explicit multivariable regressions, higher Ae. aegypti abundance, temperature, population density and lower socioeconomic status were associated with reduced introgression. Improved characterization of Ae. aegypti abundance and other structural/environmental predictors of introgression could be used to calibrate release doses to ensure equitable benefits from Wolbachia interventions.

Brazil experienced its worst dengue epidemic in 2024, with an increase in severe outcomes among elderly individuals, highlighting the need for vaccination strategies informed by population immunity. We reconstructed state- and age-specific immune profiles by fitting an age-structured catalytic model to dengue surveillance data from 2000-2025. This inferred immune profile was incorporated into an SIR-type transmission model to project disease burden and to evaluate the public health impact of vaccine allocation strategies. We observed substantial spatial heterogeneity in accumulated immunity, which was closely associated with projected burden and optimal allocation. Strategies prioritizing states with lower historical incidence and larger susceptible populations yielded greater benefits. Under limited vaccine supply, targeting children resulted in the greatest reductions in DALYs, whereas targeting elderly populations achieved smaller DALY reductions but larger reductions in mortality. We further showed that accelerated vaccine supply markedly increased impact, while allocation choices remained critical when availability was constrained.

Routine infant vaccination has helped reduce cases and deaths from diphtheria, tetanus, and pertussis globally. However, these diseases continue to pose serious health risks as protective immunity wanes over time. Three booster doses of diphtheria-tetanus-pertussis-containing vaccine (DTPCV) administered from 12-months to 15-years of age increase duration of protection beyond childhood. Growing demands on government health spending underscore the importance of understanding the health and economic impact of vaccines prior to introduction. Using an integrated multi-disease epidemiological-economic model, we estimated the health impact (cases averted, deaths averted, and changes to population immunity) and budget impact of introducing DTPCV booster doses in Uganda. Compared to no DTPCV boosters, introducing all three booster doses is projected to result in 2.2 times the proportion of the population protected against symptomatic diphtheria and 2.8 times against tetanus infection among Ugandans under 15 years of age by 2039. Compared to introduction of the early childhood booster (EC) at 18 months of age, introducing all three DTPCV boosters simultaneously is projected to avert 3.2 times the number of tetanus cases over fifteen years at 2.4 times the incremental cost. The projected government vaccination cost per planned dose was USD 0.58 for simultaneous introduction of all three boosters compared with USD 0.68 for the EC booster alone. The average annual incremental cost of all three DTPCV booster doses is USD 2.79 million. Under modelled assumptions, simultaneous introduction of all three DTPCV booster doses in Uganda provides the greatest health gains, with a lower government vaccination cost per planned dose than introduction of the EC booster alone, but may still pose affordability challenges for Ugandas government.

Tick-borne disease risk reflects the combined influence of vector abundance, pathogen prevalence, human exposure, and seasonal activity, yet these components are rarely integrated at the county level. We developed species-specific ecological risk scores for three medically important tick species (Acari: Ixodidae): Amblyomma americanum (L.), Dermacentor variabilis (Say), and Ixodes scapularis Say, across all 102 Illinois counties using data from 2019 to 2022. County-level predicted tick abundance and pathogen prevalence were scaled and combined using equal weights to generate primary vector-level risk scores. Robustness to the equal-weight assumption was evaluated by systematically varying the relative weights assigned to abundance and pathogen prevalence, while a separate sensitivity analysis incorporated reported tick-bite incidence where available. Associations with human disease were evaluated using negative binomial regression of tick-borne disease case counts on the corresponding risk scores, with county population included as an offset. Monthly phenology indicators were constructed by integrating human disease cases, reported tick bites, and sampled tick abundance and were evaluated in relation to temperature and precipitation. Seasonal risk was estimated by combining county-level vector risk with species-specific monthly phenology, generating monthly risk surfaces that were deployed through an interactive R Shiny application. Higher risk scores were significantly associated with greater disease case rates for each tick species. County rankings were highly stable under moderate changes in abundance and prevalence weighting. Seasonal activity differed among species, with A. americanum and D. variabilis showing concentrated warm-season risk and I. scapularis exhibiting a broader seasonal profile. These county-level seasonal risk maps identify where and when relative tick-borne disease risk is elevated in Illinois, supporting targeted prevention, surveillance, and clinical awareness.

Background: Severe malaria remains a major cause of hospitalization in malaria-endemic sub-Saharan Africa, and anemia is among its most frequent severity criteria. Data on the impact of anemia on hospital length of stay (LOS) among adults with severe malaria remain limited in Central Africa. We assessed the impact of anemia on LOS among adults hospitalized for severe malaria in Brazzaville, Republic of Congo. Methods: We conducted a cross-sectional, descriptive, and analytic study of medical records from adult patients ([&ge;]18 years) diagnosed with severe malaria (WHO criteria) and admitted to four hospitals in Brazzaville between January 2020 and December 2024. We dichotomized LOS as short (<5 days) or prolonged ([&ge;]5 days). Multivariable logistic regression, using a backward stepwise procedure, identified factors independently associated with prolonged LOS; isolated hemoglobinuria served as the reference severity category. Results: Among 523 patients hospitalized for severe malaria, 296 met the inclusion criteria. Median age was 25.5 years (IQR 20-40); 51.7% were female, and 82.1% had a low socioeconomic status. Median hemoglobin was 10.55 g/dL, and median LOS was 4 days (IQR 3-5). In multivariable analysis, prolonged LOS was independently associated with delay to consultation (aOR 1.25/day, 95% CI 1.09-1.44), isolated anemia (aOR 7.07, 1.23-40.55), convulsions (aOR 5.86, 1.81-18.97), prostration (aOR 4.42, 1.21-16.2), and impaired consciousness (aOR 4.29, 1.17-15.7). The strongest associations involved combined severity criteria: anemia with prostration (aOR 8.58), anemia with jaundice or hemoglobinuria (aOR 16.21), and impaired consciousness with anemia (aOR 33.31). Conclusions: Anemia is a major, potentially modifiable determinant of prolonged hospitalization in adults with severe malaria, with a markedly amplified effect when combined with neurologic impairment. Early anemia screening, improved access to safe blood transfusion, and reduced delays to care could shorten hospital stays and ease the burden on health systems in this setting.

We report general acceptance (79.0%) of Ebola vaccination in the Democratic Republic of the Congo (DRC) between 2023-2024 (n=5,062). Acceptance varied significantly by province with acceptance ranging from 47.6% in Kongo Central to 92.1% in Tshuapa province and was highest among healthcare workers. While Ebola vaccine acceptance and disease knowledge are relatively strong nationally in the DRC, regional differences do exist and may impact future vaccine rollout.

Japanese encephalitis virus (JEV) is a leading cause of viral encephalitis in humans in Asia. Prior to 2021, only sporadic outbreaks had been detected in Australia's tropical northern extremes. However, during 2021-23, JEV infection was identified in 45 people and in more than 85 piggeries, together with many detections in feral pigs, mosquitoes, and other livestock across Australia, including in the temperate far south. Here we estimated the spatial extent of virus transmission during the outbreak (the realised niche) and the area environmentally suitable for transmission (the potential niche). We collated a national dataset of JEV surveillance and detection in humans, mosquitoes, domestic pigs, feral pigs, and sentinel chickens from 2021-23. We combined these data with (1) previously published predictions of habitat suitability for vertebrate host and vector species, and (2) estimated densities of humans, domestic pigs, and feral pigs, in a multipart assessment of spatial risk. Our model projected broad potential environmental suitability over much of northern and eastern Australia during the outbreak period, but floodplain wetland areas in the north and the inland east of Australia had both the highest estimated environmental suitability for transmission, and the strongest evidence for virus circulation.

Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m2/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.

Abstract Background: Cyprus has transitioned into a high-alert zone for mosquito-borne viruses. This necessitates a proactive assessment of its future physicians. Following the 2022 re-establishment of Aedes aegypti in Larnaca and Aedes albopictus in Limassol, Cyprus, the island is now biologically primed for local outbreaks of dengue, Zika, and chikungunya, alongside Culex-borne West Nile virus. The study assessed medical students' knowledge and risk perception. Methods: A cross-sectional online survey administered the validated MosquitoWise Health Belief Model instrument to undergraduate-entry and graduate-entry students at a university in Cyprus in mid-2026. Results: Of 1023 students, 119 responded (11.6%), with pre-clinical students overrepresented (p<0.001). Mean knowledge was 5.43/9, stronger on mosquito biology (72.5%) than virus knowledge (54.2%). Median severity was 6.00/7 against susceptibility 4.25/7. Knowledge differed by study stage (p<0.001), correlated with severity (rs = 0.399) but not susceptibility. Conclusions: The study establishes a critical baseline for pre-clinical medical students in Cyprus. Overall, participants performed better on mosquito biology when compared to mosquito-borne viruses and how they spread. Our findings highlight the value of integrating theoretical microbiology with clinical practice in medical education to enhance physicians' preparedness for the changing landscape of newly emerging infections in Cyprus and across Europe as a whole. Key Words: Arboviruses, Cross-Sectional Studies, Cyprus, Health Belief Model, Medical Students, Risk Perception.

Introduction: Acute gastroenteritis (AGE) is a cause of childhood morbidity and may be associated with human adenovirus (HAdV) infection. This study aimed to investigate the occurrence of HAdV in fecal samples from children with AGE in Salvador, Bahia, Brazil, as well as to molecularly characterize the identified strains and evaluate their cytopathic effects in cell culture. Methods: A total of 131 samples were analyzed using the nested polymerase chain reaction (Nested-PCR) technique. Molecular characterization was performed through Sanger sequencing and phylogenetic analysis, while Vero cell cultures were used to investigate the occurrence of cytopathic effects. Results: Of the samples analyzed, 13 (9.9%) tested positive for HAdV, while 118 (90.1%) were negative. The highest detection frequency was observed in children aged three years or younger, particularly those under one year of age. Phylogenetic analysis identified variants related to HAdV-F41 and HAdV-B3, revealing genetic differences and distinct clustering patterns compared with reference sequences. In cell culture, cytopathic effects were observed four days after inoculation, although further analyses are required to confirm productive viral replication. Conclusion: These findings demonstrate the presence of HAdV in the samples studied and contribute to understanding its genetic diversity and circulation in Salvador, highlighting the importance of epidemiological surveillance and further studies on its role in the etiology of childhood AGE.

The efficacy of current antiretroviral interventions for prevention of vertical HIV transmission is both a triumph and a challenge for future efficacy studies of novel agents, including long-acting antiretroviral agents. Given the effectiveness of current antiretroviral interventions, standard randomized controlled trials to assess novel interventions targeted towards further reducing vertical HIV transmission may be infeasible due to required sample sizes. To address this study design challenge, we propose a novel augmented clinical trial design, where a randomized trial with an active comparator is augmented with a concurrent observational cohort to supplement the standard-of-care arm. The proposed design and analysis can overcome sampling biases, and an associated diagnostic can evaluate potential biases from unmeasured covariates. The proposed trial design is illustrated with an example and studied further using a simulation study. In the illustrative example, an augmented trial with a 3:1 allocation ratio in the trial component yielded an unbiased treatment effect estimate, as compared to the trial component alone, and the standard error was reduced substantially. Although the total sample size of the augmented trial was larger than a similarly powered 1:1 standard trial, the sample size of the augmented trial's trial component was half the size of the standard trial and within the range of historically similar trials, thereby providing both feasibility and potential cost advantages. Although limitations with this design remain, many of these limitations can be mitigated by careful study planning and coordination. Augmented trials provide a potentially applicable solution to studying the efficacy of long-acting antiretrovirals for infant postnatal prophylaxis against HIV.

Introduction: Acute gastroenteritis (AGE) is a global public health problem and a major cause of mortality in low- and lower-middle-income countries. Human bocavirus (HBoV) is among the viral agents associated with this condition. Therefore, investigating the presence of HBoV in cases of AGE in Salvador, Bahia, as well as its prevalence and circulating strains, is important. Objective: To investigate the occurrence of HBoV infection during an AGE outbreak in Salvador. Methods: A total of 178 samples were analyzed for HBoV using nested polymerase chain reaction (nested PCR), and the amplification products were visualized by agarose gel electrophoresis. HBoV was detected in 5.7% of the samples analyzed. Conclusion: This study contributes to the understanding of HBoV epidemiology as a secondary agent associated with acute gastroenteritis during a norovirus outbreak in Salvador. Continued investigation and identification of the etiological agents involved in outbreaks are essential for evaluating the causes of AGE. These findings also highlight the need for broader diagnostic approaches and the importance of phylogenetic analysis for monitoring and controlling viral infections.

Background Despite substantial improvements in maternal and child health over the past two decades, preventable maternal and neonatal morbidity and mortality remain major public health concerns in rural Bangladesh. Community-based interventions involving Community Volunteers (CVs), Community Groups (CGs), and Community Support Groups (CSGs) have been introduced to strengthen maternal and child health (MCH) services through health promotion, community engagement, and improved linkage with primary healthcare facilities. This study explored the roles, challenges, and opportunities of these community-based platforms in improving maternal and child health services. Methods A qualitative study was conducted in Kalaroa Upazila of Satkhira District, Bangladesh, between July and October 2020. Data were collected through focus group discussions and in-depth interviews with mothers, Community Volunteers, Community Group members, and Community Support Group members. Participants were purposively selected to capture diverse experiences from intervention and comparison areas. Interviews were conducted using semi-structured guides, audio-recorded with informed consent, transcribed verbatim, translated into English, and analyzed thematically using an inductive approach. Results Participants from intervention areas demonstrated greater knowledge of birth preparedness, antenatal care, pregnancy danger signs, institutional delivery, postnatal care, and newborn care than those from comparison areas. Community Volunteers, CGs, and CSGs played important roles in identifying pregnant women, conducting household counselling, promoting skilled maternal healthcare, facilitating referrals, and strengthening community participation. Participants perceived that these activities increased maternal awareness, improved health-seeking behaviour, and enhanced utilization of maternal and newborn health services. However, persistent barriers, including socio-cultural beliefs, financial constraints, transportation difficulties, shortages of skilled healthcare providers, and inadequate logistical support for community volunteers, continued to limit equitable access to quality services. Participants recommended strengthening community awareness programmes, improving community clinic readiness, enhancing referral systems, and providing regular training and supportive supervision for community-based health workers. Conclusions Community-based maternal health interventions involving Community Volunteers, Community Groups, and Community Support Groups contribute to improved maternal knowledge, health-seeking behaviour, and utilization of essential maternal and newborn health services in rural Bangladesh. Sustaining these gains will require stronger primary healthcare services, continued community engagement, and targeted strategies to address persistent health system and socio-cultural barriers. These findings provide important evidence for strengthening community-based maternal and child health programmes in Bangladesh and similar resource-constrained settings.

Retention in antiretroviral therapy (ART) programmes remains a major public health challenge in HIV care, with loss to follow-up (LTFU) and death threatening treatment success. Because these outcomes are competing events, conventional survival methods may yield biased estimates of their incidence and associated risk factors. To estimate the cumulative incidence of LTFU and mortality and identify factors associated with these outcomes among adults receiving ART in Northern Ghana using a competing-risks framework. We conducted a retrospective cohort study of 329 adults living with HIV who initiated ART at Nalerigu Baptist Medical Centre, Ghana, between January 2013 and December 2019. Fine--Gray subdistribution hazard models were used to evaluate predictors of LTFU and death while accounting for competing risks. Cause-specific Cox proportional hazards models were fitted as a sensitivity analysis. The incidence rates were 2.2 per 100 person-months (95% CI: 1.9--2.6) for LTFU and 0.74 per 100 person-months (95% CI: 0.57--0.98) for death. At 36 months, the cumulative incidence was 50.2% for LTFU and 16.0% for death. Patients residing closer to the clinic had a lower cumulative incidence of LTFU than those living farther away (SHR = 0.68, 95% CI: 0.49--0.93), whereas higher baseline weight was associated with increased LTFU (SHR = 1.02 per kg, 95% CI: 1.00--1.04). Mortality was lower among patients receiving efavirenz-based regimens (SHR = 0.27, 95% CI: 0.15--0.50), females (SHR = 0.39, 95% CI: 0.18--0.85), and those with higher baseline weight (SHR = 0.93 per kg, 95% CI: 0.90--0.96). Findings were broadly consistent in cause-specific Cox models. LTFU was substantially more frequent than mortality among adults receiving ART in Northern Ghana. Travel distance to the treatment facility was an important barrier to retention, while ART regimen, sex, and baseline weight were associated with mortality. Expanding access to ART services through decentralized and community-based models may improve retention and support efforts to achieve HIV control targets.

Background Chronic diseases are the leading causes of illness, disability, and death worldwide, with a disproportionate burden in low- and middle-income countries. Hospitalization is a critical outcome in chronic disease management, reflecting disease severity, treatment failure, and healthcare utilization. However, data on hospitalization burden and its associated factors among chronic disease patients in Ethiopia, are limited. This study aimed to determine the rate of hospitalization and its associated factors among patients with chronic diseases attending a tertiary hospital in Wolaita Zone, South Ethiopia. Methods A facility-based cross-sectional study was conducted among 321 patients with chronic diseases attending the chronic follow-up clinic at Wolaita Sodo University Comprehensive Specialized Hospital from November to December 2022. Consecutive recruitment was used, with unique medical record numbers tracked to prevent double recruitment. Data were collected through structured questionnaires and medical record review. Negative binomial regression was used to identify factors associated with hospitalization rate, with incidence rate ratios (IRR) and 95% confidence intervals (CI) reported. A p-value < 0.05 was considered statistically significant. Results Of the 321 participants, 66% reported at least one hospitalization while on treatment, with a mean of 1.70 {+/-} 1.81 hospitalizations per patient. Drug discontinuation was the most frequently documented reason for hospitalization (39.5%), followed by disease complications (22.3%) and infections (11.7%). Multimorbidity was prevalent, with the majority (59.8%) had 2-3 conditions, and a mean of 2.40 {+/-} 1.02 chronic diseases per patient. Male sex was associated with a higher hospitalization rate, while regular physical exercise was associated with a lower number of hospitalizations. Conclusion This study found a high burden of hospitalization among chronic disease patients, with drug discontinuation being the leading documented reason. Male sex and regular physical exercise were significantly associated highlighting the need for medication adherence support programs and structured exercise programs integrated into routine chronic disease care, as well as gender-sensitive interventions.

Background Influenza vaccines have seen many changes over recent years in terms of both policy recommendations and product types. Immune responses and vaccine effectiveness vary by vaccine strain composition and product type. This study aimed to explore this variation on a regional level through examining spatial and temporal autocorrelations of vaccine uptake of different product types within Michigan from 2017 to 2021. Methods Influenza vaccine administration data from the 2017/18 to 2021/22 seasons were obtained from the Michigan Care Improvement Registry. Population size estimates for 2017 and 2019 were obtained from the Michigan Department of Health and Human Services. Age-standardized and age-stratified vaccination rates were computed. Disparate county-level vaccine uptake clusters were constructed using spatial autocorrelation indicators and spatiotemporal clusters were identified using scan statistics. Linear mixed effect models were used to study the impact of social vulnerability and urbanicity level on seasonal influenza vaccination rate. Results Vaccination incidence rates for adjuvanted, recombinant, and nasal sprays vaccines and for any vaccines increased significantly through the study period. County-level spatiotemporal clusters of type-specific uptake rates were identified. Most notably, we identified an emerging cluster with high uptake of adjuvanted vaccine radiating from Ottawa County, located in suburban Grand Rapids, and the disappearance of high uptake cluster for high-dose vaccine uptake in the area. Vaccination rates by any product type were found to vary seasonally and showed weak negative association with more rural regions. The overall vaccination rates appear to be lower among counties with higher social vulnerability in certain urbanicity levels, but social vulnerability and urbanicity were not significantly associated with overall vaccination rate during the study period. Conclusions Vaccine type-specific uptake was spatially and temporally diverse in Michigan between 2017 and 2022. Mid and Northern Michigan had consistently relatively lower vaccination rate compared to other regions in Michigan.

Introduction Despite the significant burden of Shigellosis, routine surveillance systems in resource-limited settings lack predictive capabilities to guide proactive public health responses. Consequently, we developed and evaluated the accuracy, uncertainty and computational cost of multi-horizon forecasting models for Shigella incidence among children <5 years in rural western Kenya using 16-year longitudinal incidence time-series. Methods We estimated monthly Shigella incidence using data from three pediatric enteric studies (2008-2024), supplemented with Kenya Health Information System during inter-study gaps. Incidence estimates incorporated sampling, healthcare-seeking, stool-testing, and pathogen-specific weights, with bootstrap-derived 95% confidence intervals. Predictors included Google Trends health-related indicators, climate, temporal trends, and seasonality. Forecasts at 1-, 3-, and 6-month horizons were evaluated using rolling-origin validation. Following horizon-specific predictor selection using Boruta, 14 state-space, machine-learning, and hybrid models were compared using point-forecast and probabilistic metrics, bootstrap confidence intervals, and Model Confidence Sets. Adaptive conformal prediction recalibrated prediction intervals, while Shapley Additive exPlanations assessed predictor contributions. Results Mean monthly Shigella incidence was 2.51 per 100 child-years (standard deviation=1.85). Shigella dynamics in Kenya can be forecast beyond seasonal persistence alone for up to six months reducing absolute errors by ~ 33%. However, optimal model architectures and predictor sets shift systematically across forecasting horizons. Temporal trend and recent incidence were the dominant predictors, while predictor importance shifted with forecast horizon toward syndromic, pharmaceutical, seasonal, and lagged environmental signals. Extreme Gradient Boosting performed best at 1 month (Root mean squared error [RMSE]=1.86), remained competitive at 3 months (RMSE=1.89), whereas exponential smoothing (ETS) performed best at 6 months (RMSE=2.05). Forecast accuracy declined with increasing horizon. ETS and TBATS provided the best-calibrated prediction intervals, whereas machine-learning models generally under-covered. Model Confidence Sets demonstrated horizon-dependent model distinguishability. Conclusion Horizon-specific model selection balancing predictive accuracy, uncertainty calibration, and computational feasibility could strengthen operational early warning systems for shigellosis.