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.

Aedes albopictus (Skuse), the Asian tiger mosquito, is a highly competent arboviral vector whose range has expanded substantially across the United States over the past four decades. Despite predictive models placing Nebraska within the species' climatically suitable range, its establishment status in the state has remained poorly characterized. Here, we report results from a nine-year mosquito surveillance program (2017-2025) conducted across 44 Nebraska counties in collaboration with the Nebraska Department of Health and Human Services. Ae. albopictus was detected in five counties, with sustained, annually increasing populations documented in Richardson, Douglas, and Lancaster counties. Richardson County recorded continuous detections during 2017-2025, with proportional representation rising to 60.50% of collected mosquitoes by 2025. In Douglas and Lancaster counties, temporal advancement of first seasonal detection in 2024 and 2025 provide evidence consistent with successful overwintering rather than annual reintroduction. A cumulative degree-day model predicted adult emergence in mid-May across all county-year combinations, consistently preceding trap deployment by two to seven weeks and revealing a systematic early-season surveillance gap. Generalized linear mixed-effects models indicated that trap-level detection persistence, rather than urban location, was the primary predictor of yearly Ae. albopictus positivity, suggesting that current invasion dynamics are driven by focal source populations. These findings provide strong evidence for the establishment of Ae. albopictus in eastern Nebraska and highlight the need for earlier seasonal surveillance and standardized criteria to define establishment in northward-expanding vector populations.

The emergence of Highly Pathogenic Avian Influenza (HPAI 2.3.4.4b) in dairy herds in 2024 across 19 states in the United States of America has raised concerns regarding the potential national and global zoonotic impact. All recent modeling efforts implemented homogenous cattle-to-cattle (both intra and inter-herd) transmission models which did not capture the real-world heterogeneity in mixing of animals, individual variations in susceptibility and infectiousness and clinical incidences across pens and lactation groups. The aim of this study was to develop a heterogenous transmission model to estimate the epidemiological parameters for intra-herd HPAI transmission on Californian dairies. We developed a validated stochastic agent-based model to estimate the epidemiological parameters for intra-herd HPAI transmission on California dairies. The hierarchical agent-based model also parameterized stochastic cattle movements within-herd to simulate real dairy management practices. A cow-level SEIR transmission approach was assumed during the outbreak. A novel Bayesian Optimizer with Gaussian Process (BO-GP) was fitted to the agent-based model for validation which converged within 25-40 iterations (out of 100 per farm) with minimal loss over two distinct error metrics, namely, Poisson loss function and temporal distance metric. Our optimized simulations estimated an average R0 was around 10.7-10.8 across all farms within the first 15 days of observed outbreak on four dairy farms with a mean effective transmission rate of 4.5% per contact between susceptible and infectious cows within each pen. Our model demonstrated that the movement of cows between pens ensured localized clusters of outbreaks within the sub-herds (pen population) that prolonged the overall outbreak within farms. We estimated the total duration of infection between 14.5 and 28 days, which is higher than the estimates from the homogenous models. With an integrated hierarchical agent-based model combined with Bayesian approximation, we produced actionable insights on the epidemiology of intra-farm spread of HPAI within cow herds, thereby guiding both future model development and applied disease control strategy.

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.

BackgroundIn Ethiopia as other Sub-Sharan African countries malaria in pregnancy is a major public health threat particularly in the rural communities. Immunosuppression during pregnancy increases the risk of placental malaria; this, in turn, leads to anemia, low birth weight, preterm delivery, and stillbirth, causing severe complications that pose a life-threatening risk to both the mother and fetus. Hence, this study is aimed to assess the prevalence of malaria, and associated factors among pregnant women attending antenatal clinics in Damot Gale district, South Ethiopia. MethodAn institutional-based cross sectional study was conducted from March 1 to May 30, 2024. A multistage sampling technique and pre-tested semi-structured questionnaires were used for data collection. Using standard parasitological methods, blood samples collected from 389 participants were analyzed through microscopic examination of Giemsa-stained thick and thin blood films. Logistic regression was used to assess factors associated with malaria. Adjusted odds ratio with 95% confidence interval was calculated and P-value < 0.05 was considered statistically significant. ResultsIn this study the prevalence of malaria among pregnant women was 10.5% (95% CI: 7.7-13.6%). Among the malaria-positive pregnant women (9%) were P. falciparum infected, followed by P. vivax (1.3) and mixed infections (0.2%). In the multivariate analysis, multigravdae (AOR = 0.358; 95% CI: 0.14-0.92), utilization of LLINs (AOR = 0.286; 95% CI: 0.119-0.687) and use of IRS (AOR = 0.068; 95% CI: 0.027-0.172) were significantly associated with malaria among pregnant women. ConclusionMalaria is still a public health problem among pregnant women in Damote-gale district. The present study indicated that adequate distribution and proper utilization of bed nets In addition seasonal proper spray of IRS might be helpful to prevent and control malaria.

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 [&ge;]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.

Background Malaria and HIV remain major causes of illness in sub-Saharan Africa, accounting for 94% of the global malaria burden and over two-thirds of the global HIV burden. HIV-related immunosuppression increases susceptibility to malaria, with a higher malaria burden of up to 47% and severe malaria complications compared to HIV-negative individuals. Socio-demographic factors, individual knowledge, attitude, and perception are recognized determinants of malaria prevention behaviours, but no study has modelled their combined contribution, and there is scant research on these factors among people living with HIV. We assessed the level of knowledge, attitudes, and perceptions towards malaria, and identified the predictors of malaria prevention practice among HIV-positive individuals in Kampala, Uganda. Methods This cross-sectional study enrolled 620 HIV-positive patients attending the ART clinic of China-Uganda Friendship Hospital, Naguru, selected by systematic random sampling. Data collection was conducted from 21st July 2025 to 18th August 2025 using a structured, interviewer-administered questionnaire that measured socio-demographic characteristics, knowledge, attitude, perception, and the practice of malaria prevention. Associations were assessed using Mann-Whitney U, Kruskal-Wallis H, and Spearman correlation. The independent predictors of good malaria prevention practice were identified using binary logistic regression. Results Participants had a mean age of 34.8 years, were predominantly female (68.9%), Baganda (38.1%) by tribe, and the majority had a secondary level of education(46.0%). Most had good knowledge of malaria (97.3%) and a positive attitude (90.5%), while 57.3% held a positive perception of malaria risk and prevention; only 62.6% reported good malaria prevention practice, and most prevention methods used were sleeping under a mosquito net (71.1 3%) and closing windows early in the evening (70.3%). In regression analysis, knowledge (adjusted odds ratio [AOR] 1.198, 95% CI 1.03-1.40, p = 0.023) and attitude (AOR 1.101, 95% CI 1.04-1.17, p = 0.001) independently predicted good practice, while perception did not (AOR 1.00, 95% CI 0.96-1.04, p = 0.994). Scores of Attitude, perception, and malaria prevention practices varied significantly, though non-linearly, by education level, and were highest among non-educated participants. Conclusions Despite near-universal knowledge and predominantly positive attitudes in this study, more than a third of HIV-positive participants did not practice adequate malaria prevention, and perception did not independently predict malaria prevention practice once knowledge and attitude were accounted for. Programmes seeking to close this know-do gap should pair health education with structural support for prevention tools rather than education alone.

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.

Introduction: Nigeria continues to report one of the highest burdens of diphtheria globally, with Kano State accounting for a disproportionate share of cases and deaths. Understanding epidemiological patterns and mortality determinants is essential for guiding targeted interventions. Objectives: To describe the distribution of diphtheria cases in Kano State by socio-demographic and clinical characteristics, Local Government Area, and month of reporting, and identify independent predictors of mortality. Methods: We conducted a retrospective cohort study of 21,369 patients with clinically compatible and laboratory-confirmed diphtheria using secondary data from medical records (2022-2025). Descriptive statistics summarized patient characteristics and disease distribution. Associations with mortality were assessed using chi-square or Fishers exact tests. Multivariable logistic regression identified predictors of mortality, reported as adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Results: Of 21,369 patients, 13,557 (63%) were female, with a median age of 11 years (IQR: 7-13.6). Children aged 5-9 years accounted for 29% of cases. Prior contact with a case was reported in 2,633 (12%) patients, while 168 (1%) were laboratory-confirmed. Overall, 13,468 (63%) patients were unvaccinated and 5,381 (25%) fully vaccinated; Diphtheria antitoxin DAT was administered to 2,035 (10%). Cases occurred in all local government areas (LGAs), with four accounting for 60% of cases. Transmission occurred year-round, peaking in March 2024 and August 2023 and 2025. Overall, 1,131 deaths occurred (CFR: 5.3%). Compared with patients aged [&ge;]20 years, younger age groups had higher odds of mortality: 0-4 years (aOR = 26.74, 95% CI: 17.64-42.72), 5-9 years (aOR = 19.77, 95% CI: 13.17-31.33), 10-14 years (aOR = 8.21, 95% CI: 5.41-13.13), and 15-19 years (aOR = 2.46, 95% CI: 1.45-4.26). Prior contact with a case was associated with lower odds of mortality (aOR = 0.42, 95% CI: 0.30-0.55), whereas laboratory confirmation (aOR = 2.33, 95% CI: 1.48-3.56) and DAT receipt (aOR = 2.55, 95% CI: 2.19-2.96) were associated with higher odds. Prior vaccination was associated with lower odds of mortality among fully vaccinated (aOR = 0.52, 95% CI: 0.44-0.61) and partially vaccinated patients (aOR = 0.61, 95% CI: 0.47-0.80). Conclusions and recommendations: During the study period, diphtheria was more common among younger children, females, and the unvaccinated. Although concentrated in a few LGAs, transmission was widespread and varied seasonally. Mortality was associated with younger age, laboratory-confirmed infection, and use of diphtheria antitoxin, whereas vaccination and prior contact were protective. Reducing the burden requires sustained efforts to strengthen routine immunization, implement targeted vaccination campaigns, ensure early detection and prompt treatment, and improve contact tracing and case management.

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.

ABSTRACT Background: Poliomyelitis remains a major public health concern where population immunity is incomplete and circulating vaccine-derived poliovirus (cVDPV) persists. Although Nigeria interrupted wild poliovirus (WPV) transmission in 2020, cVDPV cases continue to pose challenges, particularly in parts of northern Nigeria. Modern control strategies require a synergy of routine immunization, supplementary campaigns, disease surveillance, and community trust. Methods: This multicentre descriptive cross-sectional study evaluated community knowledge and attitudes towards polio immunization across 37 Local Government Areas (LGAs) in 20 states and the Federal Capital Territory (FCT). A multistage sampling strategy was utilized to select 1,850 adult respondents (50 per LGA) spanning rural, semi-urban, and urban settlements. Results: Overall, 40.4% (n = 747) of respondents demonstrated good knowledge, while 58.4% (n = 1,080) displayed positive attitudes towards polio immunization. A striking disparity was observed across residence classifications: respondents in urban/semi-urban LGAs exhibited significantly higher levels of good knowledge (51.7%, 569/1,100) compared to those in rural LGAs (23.7%, 178/750; {chi} = 144.00, df = 1, p < 0.001). Main sources of information were Questionnaire responses (53.6%) and community and Traditional leaders(17.2%). Conclusion & Recommendations: Substantial knowledge deficits persist in rural northern Nigerian communities despite generally favorable attitudes. Interventions must prioritize localized risk communication, involvement of traditional/religious leaders, strengthening routine primary healthcare integration, and targeting zero-dose children in hard-to-reach areas. Keywords: Poliomyelitis, Oral Polio Vaccine, Vaccine Hesitancy, Northern Nigeria, Community Health, Routine Immunization.

The radical cure of Plasmodium vivax requires treatment of the dormant liver stages with either primaquine or tafenoquine but is constrained by the risk of severe hemolysis in patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency. A revised case-management package, New Primaquine Treatment (NPT), was designed to support safe radical cure in Indonesia, and included G6PD screening, targeting high dose primaquine and early clinical review. A decision-tree model was constructed using individual-level data from a study, that treated patients with 7mg/kg primaquine according to their G6PD activity: primaquine administered over 7 days (G6PD normal individuals), 14 days (individuals with intermediate G6PD deficiency), or 8 weeks (if severely G6PD deficient). The model incorporated costs, adverse events, and P. vivax recurrence over a six-month time horizon. A business-as-usual comparator was created using historical P. vivax recurrence data for Indonesia overall and the three provinces separately. The primary outcome was disability-adjusted life-years (DALYs) averted. Costs were analyzed from health system and societal perspectives, and incremental cost-effectiveness ratios (ICERs) were compared with Indonesias Health Technology Assessment recommended willingness-to-pay thresholds of 1 and 3 gross domestic product per capita (US$4,925 and $14,475). One-way and probabilistic sensitivity analyses were conducted to assess uncertainty. Overall NPT averted 0.0011 DALYs per patient with an incremental cost of US$7.40 per patient from a health system perspective. This resulted in an ICER of US$6,636 per DALY averted, which was not cost-effective at the $4,925 threshold. Cost-effectiveness varied across settings: from US$5,098 per DALY averted in Papua to US$20,051 per DALY averted in southern Sumatra and US$80,825 per DALY averted in northern Sumatra. The ICER reduced when the societal perspective was included, with NPT cost-effective in Indonesia overall ($2,261/DALY averted) and in Papua ($675/DALY averted). The risk of P. vivax recurrence and intervention costs were the most influential parameters on the ICER. Overall, NPT was between the 1-3x GDP per capita cost-effectiveness thresholds in Indonesia; however, cost-effectiveness varied significantly across settings, indicating that NPT may not be an optimal use of resources in areas with low incidence.

BackgroundNipah virus (NiV) is a zoonotic pathogen in the Henipavirus genus that causes severe, often fatal disease in humans. The World Health Organization and the Coalition for Epidemic Preparedness Innovations (CEPI) have designated NiV as a priority pathogen with pandemic potential. While CEPI is funding research on medical countermeasures, including vaccines and monoclonal antibodies (mAbs), there remains limited understanding of how at-risk countries will use them. This study aims to address this gap through targeted interviews and demand forecasting for 10 countries: Australia, Bangladesh, Cambodia, India, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. Methodology/Principal FindingsInterviews with country and global stakeholders gathered data on regional sentiment, financing, and affordability. Profiles were developed to summarize each countrys perceived outbreak risk and their likely use of countermeasures. Demand was estimated by integrating these perspectives into models of likely country-level responses to three NiV outbreak scenarios: Expected, Amplified, and Extended. In the Expected scenario, countries focused on reactive use with global annual demand ranging from approximately 800 to 5,000 doses for vaccine-only, mAb-only, and combination interventions. Ring strategies were preferred given outbreak size and infrequency. Demand was highest for vaccine-only and combination interventions, with lower demand for mAbs-only due to affordability concerns and less familiarity in Bangladesh and India. In Amplified and Extended scenarios, countries expanded their responses to include preventive campaigns for healthcare workers and rural populations. These campaigns would require approximately 410,000 and 6,300,000 doses, respectively, if introduced in all 10 countries. Conclusions/SignificanceThis study has revealed existing sentiments regarding Nipah disease and interventions and modeled demand across three outbreak scenarios. Given global annual demand based on current epidemiology, Nipah countermeasure markets are unlikely to be commercially viable solely on routine country-financed demand. Instead, market health will require external financing and stockpile mechanisms to maintain demand between sporadic outbreaks. Author SummaryNipah virus (NiV), which causes severe and often fatal disease in humans, is recognized by the Coalition for Epidemic Preparedness Innovations (CEPI) as a priority pathogen with pandemic potential. In response, CEPI has supported the development of vaccines and monoclonal antibodies (mAb). However, limited evidence exists on how at-risk countries will deploy these medical countermeasures. We interviewed key decision-makers across 10 at-risk countries, along with global experts on NiV, to better understand disease prioritization, financing and affordability considerations, and countermeasure preferences. Interview findings informed the development of a demand forecast in response to Nipah outbreaks of varying intensity. At expected outbreak levels, countries focused their response on reactive strategies given outbreak size and infrequency. As outbreaks grew in size, countries considered expanding their response to include preventive campaigns targeting healthcare workers and at-risk, rural populations. This study provides new insights into country-level perspectives on NiV and medical countermeasures and quantifies expected demand across three outbreak scenarios and 10 countries. Our findings can provide a foundation for the strategic development of an international Nipah countermeasure stockpile, designed to address episodic NiV outbreaks and enhance pandemic preparedness.

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.

While mosquito invasions and associated pathogens are increasingly prominent in Europe, evidence gaps remain for many northerly regions where proactive management interventions may be most effective. At the regional periphery of Europe, there remains a significant knowledge gap concerning mosquito vector distributions in Northern Ireland. This study aimed to address this major gap by systematically surveying larval and adult mosquito populations in key habitats (ponds, reedbeds, saltmarsh, wet grasslands, wet woodlands, and urban gardens). We further identified environmental drivers of important vector species abundance and screened collected specimens with molecular techniques to identify presence of cryptic human-biting vector species. In Northern Ireland, mosquitoes (including potential bridge vectors of West Nile and Usutu viruses) were found to be widely distributed. Between May and August 2025, a total of 2430 mosquitoes (951 adults and 1479 larvae) were collected over 196 trap nights and 76 larval collections. Collections encompassed 17 species, with Culex pipiens/torrentium being the most widely distributed and abundant taxon recorded. Mosquito abundances were greatest in reedbed habitats, related negatively with rainfall and peaked in June and July. A subset of Culex pipiens/torrentium mosquitoes were identified to species/biotype level using PCR, with the majority (89.3%) identified as Culex pipiens pipiens and 9.3% as Culex torrentium. Importantly, the first detections of Culex pipiens/molestus hybrids (1.8%) on the island of Ireland were found. This work underscores the wide, yet previously undocumented abundance and distribution of potential zoonotic vectors in Northern Ireland and provides an important baseline for management planning and future research, while contributing to broader understandings of environmental population drivers and distributions.

In England and Wales, Usutu virus (USUV) was detected in 2020 and is now established. West Nile virus (WNV) has so far only been detected in a single location, in two Aedes vexans mosquito pools sampled during 2023 surveillance. Given the growing threat to the UK from Culex-borne viruses there is a need to undertake risk assessments to contribute to preparedness and surveillance strategy for both viruses across human and animal health sectors. Here, we present the first application of a mechanistic R0-based model, incorporating temperature dependence and combining data on vector species distribution with projected future climate scenarios, to assess transmission suitability for WNV and USUV across England and Wales. Under current climate conditions, the two viruses showed comparable spatial patterns, with risk concentrated most heavily in the southeast along the Thames estuary and extending into Kent, Essex and Surrey, as well as around Cambridgeshire and adjacent counties, and across Yorkshire, Nottinghamshire and Lincolnshire. This pattern broadly corresponded with the cumulative distribution of Culex mosquito abundance established in our earlier work (Culex pipiens pipiens, Culex pipiens molestus and Culex torrentium). Both viruses were projected to show increasing transmission suitability risk over time, with substantially steeper increases under Representative Common Pathway (RCP) 8.5 then RCP 4.5. Equine WNV cases were predicted to be most likely in southeast England, in particular around Newmarket, driven by the region's dense horse population. Among the human population, London was identified as the highest-risk area, with Liverpool and Manchester also showing elevated risk levels, driven by a combination of high human and mosquito distributions. When human population distributions were age-adjusted to account for the proportion of over 60 years-olds, there was elevated risk in coastal regions, particularly in the east (Norfolk and Suffolk) and southeast (Kent) of England. The geographic distribution of positive mosquito and bird USUV cases recorded in 2023 and 2024 broadly overlapped with areas predicted to have higher USUV suitability, providing validation for the model's spatial outputs. By characterising relative spatial transmission suitability risk, this work adds to a growing understanding of where arbovirus emergence and spread are most likely across England and Wales, and can support decisions around resource allocation, targeted surveillance efforts, and public health readiness. The results also underscore the importance of incorporating climate change and vector ecology into future modelling work, given their likely influence on how arbovirus risk evolves over time.

Background. Public-health use of influenza surveillance - situational awareness, planning for clinical surge, and issuing advisories or warnings - needs more than an accurate point estimate of next week's count. What matters operationally is whether a rise is caught early, whether the direction of change is right, and whether an alert threshold is about to be crossed, all with honest uncertainty. For such use a forecast must also respect reporting delay, later data revision, and the calibration of its prediction intervals. Using Japan's sentinel surveillance, we evaluated short-term probabilistic forecasts that respect the data release history, and we measured what adding other surveillance series contributes, focusing on the properties that matter for public-health decisions. Methods. The target was the number of influenza reports per sentinel site in each of the 47 prefectures. For each forecast we predicted, as quantiles, the value 1-4 weeks after the most recent observed week. We compared three models: a ridge regression trained jointly across prefectures; a gradient-boosting quantile regression (GBQR) that learns from many surveillance series; and their equal-weight combination on the log scale. Six seasons were used to develop the models. The 2025/26 season was held out as a temporal evaluation period after the specification was fixed; because its epidemic profile had already been seen, it is not a fully independent prospective test. We scored forecasts with the weighted interval score (WIS) and checked prediction-interval coverage. For the Japanese target series we used the value first published for each week; some auxiliary series were taken as retrieved and therefore include later revisions. Results. In 2025/26, the combination's WIS relative to a persistence forecast was 0.841, 0.811, 0.794 and 0.818 at horizons of 1-4 observed weeks - that is, 16-21% lower than persistence. Coverage of the 80% prediction interval was 79.7%, 77.1%, 74.5% and 75.1%, and of the 95% interval 94.3%, 93.4%, 92.6% and 91.8%. Adding auxiliary series improved the GBQR over the development period. However, on the original scale the combination's edge over ridge regression was not statistically clear, and in some low-level rising phases the combination did worse than ridge. Conclusions. Over the period studied, models that share information across regions scored better than a persistence forecast. For public-health use, however, the operative questions are the real lead time once reporting delay is accounted for, whether rises from low levels and threshold exceedances are caught in time, and whether the upper prediction intervals are wide enough; on these, the present evidence is not yet sufficient. The 2025 change to the sentinel system also means that pre-change advisory and warning thresholds cannot be read mechanically. A prospective evaluation with strictly controlled data availability is needed before such forecasts are used to support advisories or planning.

Seasonal flooding in Adamawa State, Nigeria damages health facilities, breaks supply chains, and displaces health workers and communities, while increasing health needs. Sexual and reproductive health (SRH) services are often deprioritized, yet evidence on how they are sustained remains limited. We examined how SRH services were sustained during recurrent flooding. We conducted a qualitative descriptive study in the flood-prone Local Government Areas of Numan and Fufore. We held eight focus group discussions with women and girls and 20 key informant interviews with health providers, supply chain actors, and program implementers. Flooding closed or damaged health facilities, broke supply and cold chains, and displaced health workers. Participants linked these disruptions to unattended births and to rising hemorrhage, stillbirth, miscarriage, and genital infections. Service continuity depended less on the formal health system than on anticipatory, community-led adaptation across three phases. Before floods, stakeholders mapped risk, pre-positioned commodities, trained women in contraceptive self-injection, and dispensed medicines in advance. During floods, care shifted to mobile outreach, task-sharing, transport by canoe and boat, and community-led referral. Community health workers, traditional birth attendants, Ward Development Committees, and women's groups reached cut-off communities. Across seasons, adaptations evolved toward cash transfers, savings groups, local reusable-pad production, and decentralized commodity hubs. Continuity relied heavily on unpaid community labor and women's own resources. Sustaining SRH services in flood-prone settings requires institutionalized preparedness, decentralized supply, empowered communities, and protected health financing. Community-led models offer a transferable approach to health security in a changing climate.

In sub-Saharan Africa, human and animal health is threatened by African trypanosomoses. These diseases are caused by trypanosomes that are transmitted primarily by tsetse flies. Vector control remains one of the most effective strategies for reducing disease transmission, but requires a minimum level of knowledge of the population biology, ecology and dispersal patterns of the targeted vectors. In this respect, population genetic approaches using appropriate polymorphic genetic markers can provide valuable tools to inform and optimize control strategies. Senegal is currently engaged in a national tsetse control programme and has been identified as a study country within a European Union-funded research initiative, COMBAT (controlling and progressively minimizing the burden of animal trypanosomosis). Baseline entomological studies are currently underway in the Sine Saloum (Southern Senegal). This preliminary study aimed to characterize the population genetic structure and connectivity of tsetse fly species present in Southern Senegal, Glossina palpalis gambiensis and G. morsitans submorsitans, in order to assess their population sizes (geographically and demographically), population densities and dispersal capacities. The two species exhibited markedly contrasting population structures. The first, G. p. gambiensis, displayed an isolation by distance with rather dense subpopulations exchanging immigrants at short distances (1.6 km/generation) and continuously from Sine-Saloum to Casamance, in line with the apparent continuity of the mangrove network found along this coast. In contrast, G. m. submorsitans presented a relatively dense population over a 75 km wide area, fragmented into sparsely distributed, very dense and interconnected pockets. These findings indicate that G. p. gambiensis likely constitutes a large metapopulation comprising 3266 effective individuals on average (and up to 7765), whereas G. m. submorsitans appeared as a single and large population, scattered in small pockets that could be readily replenished by immigrants from distant areas in case of control. These results suggest that elimination is not a realistic option for any of these two populations. Alternatively, localized integrated pest management is likely to be the most effective approach for controlling the negative effects of these biting flies on domestic animals, by reducing trypanosome transmission. However, further entomological investigations and the use of more informative genetic markers are needed to obtain a more precise understanding of the epidemiological processes involved.