Vaccine: X

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.

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.

Background: Filoviruses, specifically Ebola virus (EBOV), Bundibugyo virus (BDBV), and Marburg virus (MARV), have been the etiologic agents of multiple outbreaks of severe disease in the Democratic Republic of the Congo (DRC). Two EBOV-specific vaccine regimens have been approved for use in outbreak scenarios, including the Ad26.ZEBOV/MVA-BN-Filo (Zabdeno/Mvabea) two-dose vaccine, where the MVA-BN-Filo booster dose contains EBOV, MARV, and Sudan (SUDV) virus glycoproteins (GPs) and the nucleoprotein from Tai Forest virus. While long-term immunogenicity of up to two years has been found in clinical trial settings, limited real-world data exists. Methods: Using a multiplexed immunoassay, samples (n=698 at baseline) collected in Mbandaka, Equateur province, DRC, between September 2023 and October 2024 were assessed for seroreactivity to six filovirus antigens (1 BDBV, 2 EBOV, 2 MARV, and 1 SUDV) at three distinct periods: baseline/pre-vaccination, 6-8 weeks post-first dose (Zabdeno), at booster administration (Mvabea), and one-year post-boost dose. Results: Substantial filovirus seroreactivity was found at baseline, with 48.7% (n=340/698) of individuals being seroreactive to at least one virus antigen. High baseline seroreactivity was found against BDBV GP (31.1%, n=217/698), with lower baseline seroreactivity to EBOV GP (15.5%, n=106/698), comparatively. Overall EBOV GP seroreactivity increased to 66.8% (n=376/563) at one year-post vaccine boost and 57.6% (n=250/434) of participants were seroreactive. Despite the booster dose inclusion of SUDV GP and MARV GP, there were no substantial increases in reactivity against either antigen at subsequent timepoints. Overall filovirus seroreactivity increased at all timepoints for the entire cohort, although filovirus reactivity decreased over the study period for those who were seroreactive at baseline. Findings: These data highlight detection of significantly elevated seoreactivity to EBOV GP following first-dose administration of Ad26.ZEBOV, which remained relatively stable one-year post-booster dose administration. Additionally, this study identifies high levels of baseline seroreactivity to BDBV GP despite no previous documented outbreaks in this region of DRC. These data suggest that vaccination with the Ad26.ZEBOV-MVA-BN-Filo vaccine induces stable seroreactivity against EBOV GP, but not to other filovirus antigens.

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.

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.

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.

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.

To deal with the COVID-19 pandemic, Denmark implemented an aggressive program aimed at controlling the pandemic which included both testing and contact tracing programs. The large amount of data collected in Denmark on the pandemic and its integrated nature made it possible to investigate the effectiveness of the testing and contact tracing effort. The results of that investigation and a discussion of the effectiveness and limitations of the different control efforts are reported herein, as are lessons learned concerning possible improvements for the future. The analysis is limited to the period from the start of the COVID-19 pandemic in Denmark (late Feb. 2020) into May 2021, at which time the impact of vaccination intervention was already playing a role with ~25% of the Danish population at least partially vaccinated. From the available data sets we estimate the national Infection Detection Efficiency (IDE) starting around July 1, 2020, the time at which the national infection detection program started to be implemented in a more robust form. The results rely on daily COVID-19 hospital admissions, PCR test results, and anti-body prevalence values for the Danish population. We find that for the long-term average, the combined Danish national testing and contact tracing program identified on average about 55 to 60% of the infected individuals during the period from Sept. 1, 2020, into early May 2021. However, higher infection detection efficiencies were achieved in localized areas for short time intervals. Our investigations further indicate that the Danish testing and contact tracing program, which was among the most ambitious in the world, could have had a better balance between voluntary probing on the one hand and focused contact tracing and targeted testing on the other hand. As typically implemented, it proved to be largely ineffective in controlling the pandemic. However, in at least one case when it was implemented in an enhanced and focused mode, it was able to bring a large local outbreak that dominated the country's cases under control. We have compiled a list of lessons learned regarding the use of contact tracing procedures to control potential future pandemics before vaccinations become available.

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.

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.

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.

Background: The relationship between recent viral infection and subsequent susceptibility to, or protection against, other viruses remains unclear, particularly across ages and symptom status. Methods: A prospective cohort study enrolled participants aged 6 months to 49 years in Washington and Oregon, USA, 2022-2024. Weekly nasal swabs were tested for SARS-CoV-2, respiratory syncytial virus (RSV), and influenza A/B; additional swabs were collected during symptomatic illness and were also tested for parainfluenza (PIV) 1-4, endemic human coronaviruses (hCOV), adenovirus, human metapneumovirus, human rhinovirus (hRV), and enteroviruses. Proportional hazards regression models were used to characterize associations between incident symptomatic infection (illness) and history of recent illness due to other viruses (within 1-7, 8-14, 15-30, 31-60, 61-90, 91-180 days), adjusted for geographic region, age, sex, daycare/school/work attendance, household size, and number of children in the household. For SARS-CoV-2, influenza, and RSV, these analyses were repeated to study incidence of infection (including asymptomatic cases). Findings: Of 3,560 participants, 2,969 (83%) had [&ge;]1 illness over 4,299 person-years. Adjusted hazard ratios (aHRs) in the short term ([&le;]2 weeks) after an illness were predominantly below 1, indicating that recent viral illness was often associated with lower risk of subsequent illness with other viruses. Across age groups, recent hRV illness was associated with lower risk of hCOV, PIV, and RSV illness (aHRs 0.07-0.27). SARS-CoV-2 illness was associated with a higher short-term risk of adenovirus and PIV illness (aHRs 3.20-3.33). In children aged 6 months-4 years, recent influenza illness was associated with higher short-term risk of SARS-CoV-2 illness. Including asymptomatic infections generally attenuated these associations. Interpretation: Some viral illnesses may alter short-term susceptibility to subsequent viral illnesses. Interactions may differ by age and symptom status. Funding: US Centers for Disease Control and Prevention; Washington State Department of Health.

Introduction Cancer incidence is rising rapidly in low- and middle-income countries (LMICs), where diagnostic pathology capacity is constrained. AI applied to routine histopathology could strengthen diagnostic capacity and offer leapfrogging potential by embedding AI into diagnostic systems as they are built up. However, without empirically identifying implementation determinants in LMIC cancer-diagnostic settings, AI solutions risk being poorly aligned with local constraints, limiting impact or exacerbating existing disparities. Methods We conducted an exploratory mixed-methods pilot study across three phases: 1) a structured survey characterising the diagnostic and technical landscape and AI priorities; 2) focus group discussions (FGDs) to inductively identify implementation determinants and 3) a second survey quantifying FGD-derived themes. Twelve physicians were purposively recruited (10 from LMIC, 2 from high-income countries for reference) and findings integrated through narrative triangulation. Results There was substantial heterogeneity in diagnostic and AI infrastructure that did not track consistently with country income classification. H&E staining was universally available, immunohistochemistry capacity was rudimentary at 7 of 10 sites and molecular testing absent or minimal at 6 of 10 sites. Whole-slide-imaging scanners were available at 8 of 10 sites, while graphical processing units, required for efficient AI inference, were available at only 4 of 10 sites. The participants would prioritise use of AI for cancer screening, cancer diagnosis, and biomarker prediction from H&E slides. Six implementation determinants were identified: AI literacy, governance frameworks, funding, evidence generation, clinical deployment, and collaboration. Financial constraints emerged as the dominant barrier across all determinants, and collaboration as an important enabling mechanism. Conclusion AI implementation readiness in LMIC cancer-diagnostic settings is highly heterogeneous and cannot be inferred from income classification, underscoring the need for institution-level assessment. Realising the leapfrogging potential of AI in this context requires coordinated progress across all determinants, with sustainable financing, and collaboration enabling the remaining determinants.

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.

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.

Background: While health system costs of COVID-19 are well documented, evidence on out-of-pocket costs to patients and families, including non-medical and time burden, is limited. This study aimed to estimate out-of-pocket medical, non-medical, and time burden of COVID-19 illness directly from patients and caregivers. Methods: Two cross-sectional surveys were fielded to national nonprobability samples of U.S. adults in Fall 2023: a personal burden survey (adult sample) and a caregiver burden survey (child sample). Surveys collected data on care setting, visit duration including travel and wait time, and medical and non-medical out-of-pocket costs. After applying quality-based exclusion criteria, 409 adult sample and 52 child sample responses were analyzed. Results: Over 87% of respondents were insured. Median out-of-pocket medical costs per visit were low, ranging from $5 (emergency department) to $10 (urgent care) in the adult sample, and from $0 (emergency department) to $75 (hospitalization) in the child sample. Median non-medical costs were $28 or less across care settings. Median time spent receiving care ranged from 90 minutes (primary care, child sample) to 300 minutes (emergency department, adult sample). Despite the relatively low reported out-of-pocket costs, COVID-related financial challenges were reported by 34% of the adult sample and 29% of the child sample, with the most common difficulty being paying non-medical bills (11% and 15%, respectively). Twelve percent in both groups reported problems paying COVID-19-related medical bills. Conclusions: In this post-pandemic non-probability sample, individual out-of-pocket costs for COVID-19 illness were relatively modest. However, time burden was substantial and one-third of respondents reported financial hardship. These estimates, including non-medical and time burden not captured in administrative data, can support more robust economic evaluations of COVID-19 prevention and treatment interventions.

Background HPV-vaccination prevents HPV-related cancers, but uptake remains suboptimal. In the Netherlands, a catch-up campaign invited 18-27-year-olds for an additional cost-free opportunity to initiate or complete their HPV-vaccination in 2023-2024, which led to 24% of this invited population getting vaccinated. As young adults increasingly seek health information online, understanding online questions, concerns and misinformation in response to the campaign may help improve future vaccination efforts. Supplemental to overall evaluation of the vaccination campaign, we piloted online social listening processes to generate an insight report for Public Health Service (PHS) Amsterdam. Objective This study piloted online social listening processes at the PHS Amsterdam to identify actionable insights into questions, concerns and misinformation surrounding the HPV-vaccination catch-up campaign among young adults. Methods Upon inventory of potential platforms and data sources, a retrospective online social listening analysis was conducted across the platforms Instagram, Facebook, and X, collecting data from PHS, the National Public Health Institute for Public Health and the Environment (RIVM), the Dutch public broadcasting foundation (NOS), and LINDA.meiden sources from January 1, 2023, to June 1, 2024. Publicly available posts, comments, and engagement concerning HPV-vaccination were manually collected, and inductively coded. Themes were assessed for risk, based on expected potential harm and observed reach, and used to develop recommendations. Results A total of 821 posts and 5157 comments were collected and analysed. Ten recurring themes were identified across varying levels of risk. Two themes were classified as high risk: an information gap regarding the effectiveness of HPV-vaccination and concerns about the transparency on HPV-vaccine side effects. Three themes were classified as medium risk: questioning HPV-vaccine effectiveness under certain circumstances, reduced general vaccine trust following COVID-19, and accessibility issues related to vaccination locations and service times. Two themes were classified as neutral risk: questions regarding eligibility criteria for the campaign and calls for broader HIPV-prevention measures. Finally, three low risk themes concerned questions regarding HPV-vaccine brand specifics, campaign choices, and questions about scheduling or rescheduling HPV-appointments. Comments also referred to subsequent information sources, including reliable sources (public health institutes), false narratives and misinformation. Recommendations focused on addressing questions and information gaps (i.e. improving HPV risk perception and providing more detailed HPV-vaccine information), improving communication about HPV-vaccination, and reducing practical barriers to vaccination. Conclusions Manual social listening across selected online sources provided actionable insights into the public discourse during the HPV-vaccination catch-up campaign. Results mostly reflected questions, concerns and information gaps. Although some themes were critical of HPV-vaccination, false narratives and misinformation did not dominate the discourse. Recommendations aim to reduce practical barriers and address information needs. This pilot showed that online social listening can be effectively implemented even with limited resources.

Globally, measles is re-emerging in countries that have previously achieved elimination, including the United States. As immunization rates decline, characterizing the dynamics and evolving spatial pattern of measles re-emergence is critical to inform the public health response. We analyze annual county-level measles cases and vaccine coverage data in the United States (US) from 2011-2025 and find a shift in measles epidemiology in recent years indicative of re-emergence. While outbreak risk is spatially concentrated, we find that outbreaks are increasingly spreading throughout the broader population and across counties, but targeted interventions are predicted to prevent re-emergence nationwide. During the first decade of this period (2011-2020), outbreaks were only weakly associated with county-level vaccine coverage and predominantly isolated to single counties; however, recently (2021-2025), vaccine coverage has become strongly associated with outbreak size and spread across neighboring counties has increased. These findings suggest that measles transmission is increasingly sustained across the broader population rather than only in socially clustered communities. We developed a spatial statistical model to predict outbreak risk and size in all US counties with validation over 2021-2025; the model predicted counties with [&ge;]10 cases with a sensitivity of 95% (range across 2021-2025: 75-100%) and specificity of 83% (64-98%). Mechanistic models based on county vaccine coverage alone had worse performance, particularly in predicting larger outbreaks. Using the spatial statistical model, we find that prioritizing interventions in the areas of greatest model-predicted risk (e.g., top decile of US counties) was more impactful than state-level interventions (e.g., top five states) or targeting based on low vaccine coverage alone. Achieving even modest (5 percentage point) increases in vaccine coverage in counties in the top decile of model-predicted risk reduced long-term measles risk nationwide by over 90%. Together, these findings demonstrate that predictive risk modeling to inform spatially targeted interventions can likely mitigate the re-emergence of vaccine-preventable diseases.

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.

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.