Infectious Diseases of Poverty

Wolbachia-mediated incompatible-insect technique (IIT) via wAlbB, wMel or wPip/wAlbA/wAlbB strains are promising approaches for suppressing wildtype Aedes mosquitoes and therefore Aedes-borne diseases. Yet, the effectiveness of this technique under climate change remains uncertain. Here, we evaluate the long-term robustness of male Wolbachia-infected mosquito releases to suppress wildtype Aedes aegypti and Ae. albopictus populations across future climate scenarios across diverse geographical regions. We compiled large publicly available datasets on Aedes abundance across Singapore, China, the European Union and the United States, historical and projected climatic conditions in these regions and conducted experiments to test the thermal stability of cytoplasmic incompatibility in Wolbachia-infected male Aedes aegypti and albopictus. A climatically-driven entomological model was developed and calibrated using a Bayesian approach to model observed Aedes population dynamics and infer area-specific climate-driven variation in mosquito life-history traits. We back-inferred historical mosquito abundance and projected mosquito abundance in future climate change scenarios incorporating experimental and locally inferred entomological parameters and then simulated the counterfactual implementation of IIT in these regions. We find that Aedes populations are projected to increase in most regions across all climate change scenarios from 2050-2100 even under high heat conditions in the absence of interventions. While we found that IIT can suppress wild-type populations effectively across all future scenarios and in high heat conditions, effectiveness was found to depend heavily on mosquito emigration rates, overflooding ratios, release intervals and release strategies Extensive robustness checks confirmed that the model reproduced historical temporal trends, captured the influence of individual parameters on outcome and was sensitive to changes in values of inferred parameters and implement policy. These findings demonstrate that IIT may be a robust vector control tool under future climate conditions.

This brief work discusses potential superspreading events that may occur during the World Cup in Mexico. The study is particularly focused on the city of Guadalajara due to a large recent outbreak in January and February and insufficient vaccine coverage prior to 2026. Keywords: Superspreading; measles outbreak; branching process; individual reproduction number; World Cup

Background Brucellosis is a severe zoonotic disease with pronounced seasonality and regional heterogeneity in high-incidence areas of China. Reliable forecasting tools are needed to inform prevention strategies, but the optimal modeling approach across different regions remains unclear. Principal Findings We collected monthly brucellosis incidence and 17 environmental variables from 2014 to 2024 across five high-incidence provinces: Inner Mongolia, Xinjiang, Shanxi, Heilongjiang, and Hebei. A three-step procedure--cross-correlation analysis, multicollinearity diagnostics, and stepwise regression--was used to select exogenous predictors. We then compared four time-series models: seasonal autoregressive integrated moving average (SARIMA), SARIMA with exogenous variables (SARIMAX), long short-term memory (LSTM), and LSTM with exogenous variables (LSTMX). All five provinces showed a unimodal seasonal pattern with peaks between April and July, though environmental drivers and optimal lag periods varied substantially by region, ranging from 1 to 6 months. In forecasting performance, LSTM achieved the highest accuracy in Shanxi (R2=0.925), Hebei (R2=0.876), and Xinjiang (R2=0.829), outperforming SARIMA and SARIMAX. LSTMX performed best in Inner Mongolia (R2=0.759) and Heilongjiang (R2=0.772) but showed weaker performance than LSTM in Shanxi and Hebei. Overall, adding exogenous variables did not consistently improve predictions across provinces. Conclusions Our findings demonstrate that LSTM-based models offer clear advantages for brucellosis forecasting in most high-incidence provinces, but the value of incorporating environmental predictors is region-dependent. These results support the development of tailored early warning systems and precision prevention strategies for brucellosis in high-risk areas of China.

The mosquito Aedes albopictus is a competent vector for the transmission of several arboviruses and is currently spreading across many continents. Since conventional control methods, like insecticides, often lead to environmental problems and the emergence of resistance, scientists developed alternative mosquito control strategies. One of the most used is the Sterile Insect Technique (SIT), which involves the mass release of males sterilized through irradiation. The Toxic Male Technique (TMT) is instead based on the release of genetically modified males expressing toxic proteins that kill females when they mate. Control strategies are often intended as methods to eradicate mosquito populations, yet a less ambitious and more cost-effective task is to reduce them such that the probability of transmission of viruses to humans becomes negligible. To compare the efficacy of these control strategies, we develop a mathematical model with two communicating compartments: a mosquito population and epidemiological model coupled with a human epidemiological model. As a proof-of-concept, we test the model using meteorological and entomological data for the Emilia-Romagna region. Our results indicate that the TMT strategy is more effective in lowering the probability of transmission and provides indication for the deployment of control strategies.

Background: Dirofilaria repens is a zoonotic parasite expanding unnoticed across Europe due to climate change. We hypothesised that in this process, the Carpathian Basin has a facilitating effect. Methods: Using 426 georeferenced European cases, the probability of infection occurrence was determined in relation to climatic factors, surface water availability, regional social deprivation, and stray dog population density. To analyse the potential impacts of ecological and social factors (deprivation and stray dog population density), the MaxEnt algorithm, and spatial Empirical Bayes smoothing and Bivariate Local Indicators of Spatial Association (BiLISA) index calculation were employed, respectively. Results: MaxEnt analysis revealed that the mean warmest month temperature (22.8 - 25.1 oC), winter mean minimum temperature (> -2.1 oC), and summer precipitation (28.6 - 231 mm) have the strongest impact on the probability of the parasite's occurrence in Europe. Social factors have significance in the eastern Balkans and the Carpathian Basin, but not in Western Europe. The Carpathian Basin appears to be a hotspot, similar to Mediterranean coastal areas. Furthermore, the Danube Valley acts as an ecological corridor for subtropical vector-borne parasites. Conclusions: Our findings confirm that summer warmth is the primary ecological driver of the parasite's range expansion, which is facilitated by the Carpathian Basin due to climatic and socioeconomic conditions.

During the ongoing Bundibugyo ebolavirus disease outbreak in the Democratic Republic of the Congo, we quantify introduction risk and sustained-transmission potential across the country. This identifies priority zones far from currently affected areas, where rapid amplification could follow introduction and response efforts should be focused.

ObjectivesTo estimate the pooled prevalence of Wolbachia infection in biting midges (Ceratopogonidae) across Southwest Asia and to evaluate ecological and biological factors associated with infection patterns. Study DesignSystematic review and meta-analysis. MethodsA comprehensive search of international and regional databases (PubMed, Scopus, Web of Science, Embase, SID, MagIran) was conducted without date restriction. Eligible studies included those using molecular techniques to detect Wolbachia in Ceratopogonidae collected from Southwest Asia. Pooled prevalence was calculated using a random-effects model. Subgroup and meta-regression analyses were performed to assess variations by country, species, altitude, habitat type, and sex. Heterogeneity and publication bias were evaluated using I{superscript 2}, Cochrans Q, and Eggers tests in accordance with PRISMA guidelines. ResultsTwenty-four studies comprising 14,832 midges from six countries were included. The pooled prevalence of Wolbachia infection was 32.6% (95% CI: 28.4-36.9%; I{superscript 2}=78.3%). Iran showed the highest prevalence (38.2%), and Culicoides imicola was the most frequently infected species (36.8%). Higher prevalence was associated with lower altitudes (<500 m; P=0.012), rural habitats (P=0.034), and female midges (P=0.008). Limited evidence suggested the presence of cytoplasmic incompatibility and reduced bluetongue virus competence in infected midges. ConclusionsWolbachia infection is common among Ceratopogonidae in Southwest Asia and is influenced by ecological and biological factors. These findings highlight the potential of Wolbachia as a biocontrol tool in regional vector management, underscoring the need for further experimental and strain-level studies.

Abstract BACKGROUND West Nile virus (WNV) is a growing health burden in Italy. Anticipating human infection risk is hampered by the pathogen's complex ecology, highlighting the need for comprehensive early-warning tools. AIM We aimed to model municipal-level WNV risk in Italy and characterize its decadal expansion in Italy, providing a comprehensive ecological understanding of viral emergence. METHODS We applied a machine learning framework to annual human WNV case data from 2014 to 2024. The model integrated a suite of environmental, socio-economic, and macroecological predictors to generate risk projections. We evaluated the model's performance through multiple validation settings. We also performed an anticipation test for the 2025 epidemic season, using 2024 environmental data to assess the model's predictive accuracy against observed 2025 human cases. RESULTS Our model achieved robust performance (True Skill Statistic > 0.4) and captured WNV progressive expansion from 184 predicted positive municipalities in 2014 to 2,012 in 2024 (an 11-fold increase in 11 years). Seasonal minimum temperature was the primary risk driver, followed by monitoring year and population density, indicating active spatial spread. Environmental suitability consistently preceded clinical detection. Municipalities with cases in 2023-2024 exhibited significantly higher predicted suitability during 2018-2022 than those without cases (average risk 0.58 vs 0.20). Our model successfully identified emerging risk hotspots along the Adriatic coast and southern Italy before the official human spillover of 2025. CONCLUSION Embedding macroecological drivers into WNV risk modelling provides an improved understanding of drivers of rapid WNV expansion. Our model enables proactive risk mapping, surveillance efforts, and targeted public health measures.

Conventional mosquito surveillance typically relies on contemporaneous data, making it challenging to anticipate future vector surges. To support proactive vector management, this study evaluates a multi-model forecasting framework designed to generate probabilistic 1- to 4-week-ahead forecasts of Aedes aegypti relative abundance per trap night. The framework was validated using multi-year surveillance data across four US jurisdictions spanning varied environments (from subtropical to temperate and arid). We found that an ensemble approach aggregating statistical and machine learning models generally achieved the best performance across all locations and forecast horizons. Relative forecast performance improved as the forecast horizon extended from 1 to 4 weeks ahead. The most challenging data to forecast were primarily restricted to low mosquito activity periods or atypical population peaks with unusual timing or magnitude. While full integration into routine vector management workflows represents a long-term process requiring operational adaptation, this work advances forecasting research and establishes a baseline for translating these approaches into real-time applications for public health authorities, with downstream effects in mitigating the risks of mosquito-borne diseases.

BackgroundDengue remains a major public health challenge in Thailand despite decades of vector control implementation. While mathematical models have explored dengue transmission dynamics, systematic evaluation of current control strategies under realistic operational conditions remains limited. MethodsWe developed a temperature-dependent, multi-serotype dengue transmission model that explicitly incorporates three primary vector control strategies: reduction in mosquito biting rates through personal protection measures, further reduction in mosquito birth rates beyond current larval control efforts, and further increase in adult mosquito mortality beyond current adulticide application levels. Using Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC), we fitted the model to dengue hemorrhagic fever (DHF) surveillance data from nine province-year combinations representing high (Rayong), moderate (Ratchaburi), and low (Phrae) transmission settings across three years (2006, 2015, and 2017). The model accounts for four dengue serotypes, temperature-dependent mosquito dynamics, and temporary cross-protective immunity between serotypes. ResultsThe model closely reproduced observed monthly DHF case counts across all nine province-year combinations. Estimated reporting proportions ranged from 1.4% to 16.7%, with the highest values occurring in high-transmission provinces during the 2015 outbreak year. When each strategy was independently intensified by 50% relative to fitted baseline levels, reducing mosquito biting rates and increasing adult mosquito mortality consistently produced greater reductions in transmission than reducing mosquito birth rates. In the highest-transmission scenario (Rayong, 2015), a 50% reduction in biting rate from the baseline level yielded a 96.4% reduction in cumulative infections (95% CrI: 95.4-97.3%), compared with 94.3% (95% CrI: 91.8-95.6%) for a 50% increase in adult mosquito mortality and 77.0% (95% CrI: 58.6-84.6%) for a 50% reduction in mosquito birth rate. Analysis of the time-varying reproduction number (Rt) confirmed that interventions targeting adult mosquito-human contact achieved the greatest sustained epidemic suppression, although the relative ranking between bite prevention and adulticide application varied by epidemiological setting. ConclusionsUnder the uniform 50% intensification scenario tested, interventions that directly disrupt adult mosquito-human contact, whether through personal protection or adulticide application, substantially outperformed larval control in reducing dengue transmission across diverse Thai settings. These findings support prioritizing personal protection and adulticide application, while the generalizability of this ranking to other intensification levels and settings warrants further investigation.

Entomological surveillance is essential for the control of lymphatic filariasis (LF). This xenomonitoring study, conducted in 2022-2023, evaluated the effectiveness of three mosquito trapping methods to identify the most suitable tool for surveillance following the discontinuation of mass drug administration. The surveys took place in two Malian villages: Konfra (seasonal watercourse) and Siradjouba (permanent watercourse). Three techniques were compared: Pyrethrum spray catch (PSC) conducted at the end of each visit inside 30 randomly selected houses, and different collection points were chosen based on the characteristics of the study area to place the Ifakara Type C tent (Ifakara) and the gravid trap (GT). Collections were conducted simultaneously at both sites. All Anopheles gambiae and Culex spp. collected in 2022-2023 were morphologically identified and then analyzed in the laboratory for their infectious status. Data was processed using SPSS v25; Fishers exact test was used to compare proportions, with a significance threshold of p < 0.05. A total of 4,732 mosquitoes were captured (95.05% in 2022). In 2022, the Anopheles were predominant in Konfra (91.38%), while Culex predominated in Siradjouba (63.41%). In 2023, Anopheles was found only in Konfra (3 specimens), while Culex was predominant in Siradjouba (64.07%). In 2022, PSC collected 90.57% of Anopheles, Ifakara 9.43%, and GT 0%. For Culex, GT collected 53.67%, PSC 36.62%, and Ifakara 9.71%. In 2023, the few Anopheles (3) came from PSC; Culex were mainly collected by the Ifakara tent (43.29%). For FL xenomonitoring, the combination of PSC and the GT appear to be effective collection methods.

Objective: In Japan, antiretroviral therapy (ART) for individuals living with human immunodeficiency virus (HIV) is financially supported through the Physical Disability Certification System for Immunological Impairment. However, certification requires multiple laboratory assessments after diagnosis, possibly delaying ART initiation. This study examined the impact of these eligibility requirements on ART initiation using real-world clinical data. Design: Single-center retrospective cohort study. Setting: Nagoya Medical Center, Japan. Subjects, participants: A total of 568 patients who attended their first consultation between 2015 and 2019 were included. Of these, 434 were ART-naive, and 134 had already initiated ART at the first visit. Main outcome measures: ART initiation rate, time to treatment initiation, factors associated with treatment delay, and utilization of the Physical Disability Certificate system. Results: Among the 434 untreated patients, the median time to ART initiation was 42 days. Seven patients (1.6%) did not meet the Grade 4 certification requirements and remained untreated. Overall, 13 of the 568 patients (2.3%) were affected by the certification system, including those importing ART from overseas or using alternative financial support mechanisms. Non-Japanese nationality, lack of health insurance, unstable employment, and low CD4 cell counts were significantly associated with failure to initiate treatment. Among the 134 previously treated patients, 108 (80.5%) had obtained a Physical Disability Certificate. Conclusions: Although relatively few patients were affected, certification requirements may delay ART initiation among socioeconomically vulnerable populations. Further multi-center and cost-effectiveness studies are needed to improve compatibility between long-term financial support systems and rapid ART initiation strategies after diagnosis.

Locally acquired arboviral infections are an increasing public health concern in the United States. Aedes aegypti and Culex quinquefasciatus, vectors of dengue virus and West Nile virus, respectively, are established in regions where local transmission has been reported. Seasonal variation in mosquito abundance affects vector density, human-vector contact, and arbovirus transmission risk. The aim of this study is to investigate seasonal variations in Ae. aegypti and Cx. quinquefasciatus population dynamics in Miami-Dade County, Florida; Maricopa County, Arizona; and Clark County, Nevada. Monthly relative abundance, average mosquitoes collected per trap-night, normalized abundance ratios, and seasonal-trend decomposition were used to evaluate species- and location-specific seasonal patterns. Mosquito population dynamics differed by species and location. In Miami-Dade County, the two species showed seasonal turnover, with Cx. quinquefasciatus peaking during winter and spring and Ae. aegypti peaking during summer. In Maricopa and Clark counties, both species peaked primarily between August and September. Species dominance also differed by site, with Ae. aegypti more abundant than Cx. quinquefasciatus in Maricopa County and Cx. quinquefasciatus more abundant than Ae. aegypti in Clark and Miami-Dade counties. Seasonal decomposition showed that Ae. aegypti peaked earlier in Miami-Dade County than in Maricopa and Clark counties, whereas Cx. quinquefasciatus showed a spring peak in Miami-Dade County and bimodal seasonal patterns in Maricopa and Clark counties. These results suggest that mosquito population dynamics are species- and location-specific and support the use of local surveillance data to guide the timing of mosquito control and arbovirus preparedness.

BackgroundDengue has been a major health threat globally in recent years. In particular, dengue incidences continue to increase annually and the epidemic area has expanded primarily due to global warming. Therefore, effective case detection and surveillance strategies are crucial to tackle this global health challenge. In clinical practice, the rapid test kit detecting dengue non-structural protein 1 antigen and commonly referred as NS1, is widely employed for early diagnosis. However, real-world studies revealed that the sensitivity of the NS1 test kit ranged from approximately 61% to 95%. Since early diagnosis is really critical for disease surveillance in the early stage of a dengue epidemic, scientists have been working hard to develop novel diagnosis methods that can provide higher sensitivity levels. Methodology/Principal FindingsIn response to this challenge, in this study, we have developed a novel diagnosis procedure that integrates machine learning technologies with the NS1 test kit. Our experimental results revealed that we would be able to raise the sensitivity of the dengue diagnosis procedure to higher than 99% by incorporating machine learning based prediction models to screen the suspected patients with a negative NS1 result. Furthermore, the relative risks between the suspected patients who were predicted to be positive and those who were predicted to be negative exceeded 4.8. Conclusions/SignificanceThese results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to address the global health challenge caused by spread of dengue. Author SummaryThis study has aimed to enhance surveillance of the dengue disease by integrating machine learning technologies with the rapid test kit commonly employed in early diagnosis. In clinical practice, the NS1 rapid test kit is widely employed for early diagnosis. However, real-world studies revealed that a certain percentage of the patients with a negative NS1 test result, ranging from 5% to 39%, were actually infected by dengue. Since early diagnosis is critical for disease control in the early stage of a dengue epidemic, scientists have been working hard to tackle this challenge. Based on this observation, this study was launched to investigate the effects of incorporating machine learning based prediction models to further screen those patients with a negative NS1 test result. The experimental results revealed that the proposed approach was able to identify over 99% of the patients who were infected by the dengue disease. Furthermore, the risk of the suspected patients who were predicted to be positive was 4.8 times higher than the risk of those who were predicted to be negative. The experimental results illustrate that the proposed approach provides an effective and efficient diagnosis procedure to enhance surveillance of the dengue disease.

Dengue fever risk and burden has increased globally in the past decade, with record-breaking outbreaks driving high case numbers, outbreaks increasing in existing transmission suitable regions, and occurring in new locations. A combination of global change processes, including climate change, have provided the environmental backdrop for introductions and resurgences of mosquito-transmitted dengue virus. Understanding shifts in exposure risk is integral to public health preparedness. This study provides global mapping of the thermal suitability of dengue transmission for CMIP6 climate scenarios, across a range of general circulation models (GCMs), and we created spatially explicit demographic projections of transmission risk using year-matched RCP-SSP frameworks for demographic and emissions scenarios. Globally, poleward shifts in projected distributions of suitability for transmission for both Ae. aegypti and Ae. albopictus suitability are shown in both the near term (2030s) and longer term (2050). Under a 'middle of the road' climate scenario (CMIP6 SSP2-4.5), regions in Africa and Asia are the major areas driving increases in year-round (12 months) population at risk (PAR) through 2050, with an anticipated net gain in 932 million people at risk for Ae. aegypti transmission and 24 million for Ae. albopictus, which includes multiple regions losing areas of year-round suitability as temperatures exceed the higher thermal boundary for transmission. In contrast, the estimated net increase in PAR for one or more months of transmission suitability at a global scale by 2050 is 3.29 billion people for Ae. aegypti transmission and 3.30 billion for Ae. albopictus transmission. This snapshot of a 'middle-of-the-road' combination of climate and demographic driven increases in potential dengue transmission exposure emphasizes the importance of both expanding suitability in new areas, and growing populations in areas approaching and becoming exposed year-round. Globalization, urbanization, and shipping will continue to provide the potential for introductions into newly suitable areas as season lengths increase, sparking outbreaks in unexposed populations. This is compounded and becomes ever more probable as the number of people and places at year-round risk also increases. This project provides all global gridded outputs for onward mapping and reuse, to add to the toolkit to anticipate and prepare for prevention and response to dengue in a changing world.

BackgroundMosquito-borne arboviruses present persistent public health threats in Mexico. Multiple vector species are often considered to influence the local transmission of arboviral diseases; however, the structure and spatial dynamics of mosquito-arbovirus associations are unknown. MethodsWe conducted a systematic review to synthesize research investigating natural arboviral infections across mosquito taxa. PRISMA-guided search was done in PubMed, Scopus, Web of Science and Google Scholar, resulting in 46 included articles from 2007 to 2025. To delineate mosquito-arbovirus associations, spatial autocorrelation, bipartite network analysis, generalized linear mixed models (GLMMs) and comparative analysis of infection across sex and life stages were used to resolve spatial dynamics, species-specific viral detection and maintenance profiles. ResultsMinimum Infection Rate (MIR) revealed significant positive spatial autocorrelation (Global Morans I = 0.139; p = 0.016), indicating structured but diffuse spatial patterns (Local Morans I = 0.092; p = 0.045). Sampling intensity negatively correlated with the MIR (Spearman {rho} = -0.680, p < 0.001), indicating that sampling effort did not obscure the spatial structure. Elevated values were observed in a few municipalities across south-central and southeastern Mexico, where vegetation and land use interface. Network analysis (connectance = 0.40) and GLMM characterized an Aedes-centered network with broader taxonomic patterns driven by ZIKV; detection was significantly higher in Culex quinquefasciatus (OR = 1.88, p < 0.001) relative to Aedes aegypti. DENV detection patterns contrasted with other key viruses; no significant differences in transmission modes ({chi}{superscript 2} = 1.01, p = 0.315), suggesting a distinct maintenance profile. ConclusionsThis review unveils spatially diffuse and virus-specific detection patterns across heterogeneous communities in Mexico, findings that transcend Aedes-centric frameworks. These resolutions provide an evidence-based baseline that encourages an integrated, community-scale approach in regional surveillance programs. AUTHOR SUMMARYMosquito-borne arboviruses continue to threaten human and animal health across Mexico. Previous research has investigated arboviral infections and mosquito fauna as separate entities, but not their associations. This systematic review aims to resolve the spatial structure and multi-species dynamics of mosquito-arbovirus associations. We synthesized a long-term dataset of mosquito-borne virus surveillance from academic articles. Spatial models determined if localized detections were random and/or clustered with hotspots. Network and mixed models estimated the likelihood of positive arbovirus detection in mosquito species and a comparison test quantified the influence of vertical transmission on viral maintenance. Arboviral infection rates showed a diffuse spatial pattern with elevated values across urban and interface settings. Aedes aegypti shaped the mosquito-arbovirus network as expected; however, Culex quinquefasciatus showed significantly higher odds of ZIKV detection, supporting broader surveillance. These findings clarify species-specific detection and maintenance profiles across mosquito taxa, informing improved and targeted control strategies for arboviral diseases in Mexico.

Understanding the immune response against HIV-1 and the natural resistance exhibited by HIV-exposed Seronegative Individuals (HESN) offers the possibility of proposing new control strategies. Several studies suggest an important role of HLA and KIR genes in protecting against HIV-1 infection. Moreover, there is an important gap in the knowledge of these genetic factors in seronegative Latin American men who have sex with men (MSM), a population largely underrepresented in HIV immunogenetic studies. This study aimed to identify HLA and KIR genetic profile associated with potential resistance to HIV-1 acquisition, in a cross-sectional study including a cohort of 60 HIV-1-seronegative Colombian MSM at low and high risk of HIV-1 infection. The high-risk group showed a higher frequency of the HLA-B*18 allele, and a lower frequency of the HLA*B35, which have been previously associated with protection and susceptibility to HIV-1 infection respectively. Likewise, the high-risk group exhibited a low frequency of Bx haplotypes, a higher frequency of one AA haplotype and differences in KIR gene profile, with a low frequency of the inhibitory KIR2DL5 and both activating KIR2DS1, KIR2DS2 and KIR2DS5 genes. These findings suggest that host immunogenetic factors may contribute to resistance to HIV-1 acquisition in highly exposed individuals.

BackgroundHepatitis B virus infection remains a major public health challenge, particularly among people living with human immunodeficiency virus, due to shared transmission routes and the potential for accelerated liver disease progression. Molecular characterization of circulating HBV strains is essential for understanding viral epidemiology, mutation patterns, and implications for diagnostics and vaccination. MethodsThis study investigated the prevalence of hepatitis B infection and molecular characteristics of the hepatitis B virus surface gene among HIV-infected individuals receiving antiretroviral therapy in Nairobi County, Kenya. Plasma samples were screened for hepatitis B surface antigen using enzyme-linked immunosorbent assay. Hepatitis B viral DNA was extracted from HBsAg-positive samples and the surface gene region amplified by polymerase chain reaction. Amplified products were subjected to Sanger sequencing. Sequence assembly, genotype determination, and mutation analysis. ResultsThe prevalence of HIV/HBV co-infection among HIV-positive individuals was determined to be 8.97%. Genotype analysis revealed the circulation of HBV genotype A (sub-genotypes A1 and A4) and genotype D (sub-genotypes D4 and D10) among the studied population. Amino acid sequence analysis of the major hydrophilic region of the surface gene identified several mutations, with R122K and Y134F being the most frequently observed substitutions. ConclusionHepatitis B infection remains prevalent among HIV-infected individuals receiving antiretroviral therapy in Nairobi County. The circulation of multiple hepatitis B virus genotypes and the presence of mutations within the surface gene highlight the importance of continuous molecular surveillance to monitor viral evolution and its potential implications for hepatitis B virus diagnosis, vaccination strategies, and clinical management in HIV-infected populations

Dengue virus is a severe threat to global health. Novel vaccine and Wolbachia technologies offer a potential path to dengue control; however, it remains unclear how to use these approaches in tandem. Using metapopulation transmission models, we simulated future dengue burden in Brazil. We estimated that wMel releases in 300 municipalities could avert 12-22% of cases over the next 10 years, while a national vaccination campaign could avert 8-10% of cases in the total population and 39-45% within the vaccinated cohort. Projecting forward 40 years, we found wMel releases would drive up the mean age of cases beyond increases due to the ageing population and increase population susceptibility to dengue. Finally, wMel releases can help mitigate the future burden in southern Brazil where climate change is rapidly increasing dengue virus risk. These findings highlight the need to consider the two technologies in parallel to optimise efforts to combat future dengue burden.

ABSTRACT Background Dog bite injuries are a major yet largely preventable public health concern worldwide. They contribute significantly to morbidity, healthcare burden, and economic costs, particularly in emergency department .The present study aims to analyse the demographics and injury pattern of dog bite cases presenting to the emergency department of a tertiary care hospital in Chennai. Methods We conducted a cross-sectional study with dog bite injured participants attending the Causality from November 2025 to April 2026 data was collected using a structured tool including details on demographics (Age, Gender, Education) injury related characteristics , history of pure bite site of dog bite injury type, WHO bitten criteria and information to management etc. We used here non probability statistical analysis and age specific dog bite cases and independent variables were analysed using SPSS (2.0 version). Result A total of Two hundred sixteen dog bite cases were analysed in the study by period of 6 months The majority of participants were 172 (79.6%) were above 18 years and 44 (20.4) were below 18 year, 130 (60%) from rural areas and 86 (39.8%) from urban areas, 136 (63.0%) of Victims presented within a day of the bite, 61( 28.2) next day and 19 (8.8%) in after one week 66 (30.6) were bitten by own dog and 150(69.4%)were bitten by neighbour / friended dog. 124(57.4) were bitten by stray dog 92(42.6) bitten by pet dog. 117(54.2) were vaccinated dog and 99(45.8%) were not vaccinated .110(50.9) victims were injured by laceration. 26(12.0%) were injured by puncture wound.46(21.3) were injured by abrasion 10(4.6) were injured by avulsion 15(6.9%) were injured by crush injury. 156(72.2%) were had minor wound.45(20.8%) victims had moderate wound and 15(6.9%) victims had severe wound. 112(51.9%) victims were taken antibiotics.104(48%) were not taken antibiotics. 185(85.6%) victims received tetanus toxoid, 31(14.4%) were not received tetanus toxoid. CONCLUSION There is a high burden of dog bite injuries from stray dogs in India. Despite early hospital presentation in many cases gaps in first aid practices and rabies post exposure prophylaxis were evident and highlighting inadequate awareness. Key words Rabies immunoglobulin, Dog bite, WHO criteria, Anti rabies vaccine, stray Dog, wound