International journal of psychology : Journal international de psychologieQiandong Wang, Yawen Li, Yuxuan Liang, Sio Pan Hoi, Li Yi
Individuals from regions affected by infectious disease outbreaks may be stigmatized because others hold negative mental images-or mental representations-of them. This study investigated whether such outbreaks lead to the formation of negative mental representations of residents in affected areas and explored the role of disease severity in this process. Study 1 revealed that during the early stages of the COVID-19 epidemic, the public's mental representations of residents from Wuhan were perceived as less attractive than those of Chengdu residents and associated with disgust and behavioural avoidance. However, differences disappeared after the restrictions of the epidemic were lifted. The results indicate that the COVID-19 outbreak triggered stigmatization of residents in Wuhan. In Study 2, disease severity and perceived threat were manipulated, and results show that participants formed less attractive face representations of residents from areas where severe infectious diseases broke out than those from areas affected by mild infectious diseases. This proved that the severity of infectious diseases affected the extent of stigmatization towards residents in outbreak areas. These results further our understanding of the mechanisms and factors underlying stigmatization associated with affected regions and may inform effective public health strategies to mitigate stigma and support disease control efforts.
Journal of community psychologyGigi Lam, Catherine So-Kum Tang, Tiffany Sok U Siu, Tak Sang Chow
This study examined how community factors impacted well-being during the COVID-19 pandemic in China. Data were collected at two time points: Time 1 (T1) in September 2021 (N = 992) when COVID-19 cases stabilized, and Time 2 (T2) in January 2023 (N = 497) during a sudden outbreak of new infected cases. At T1, perceived community safety and sense of community directly affected depression, anxiety, and physical health symptoms, with sense of community partially mediating these effects. At T2, community factors at T1 continued to impact depression, anxiety, and physical health symptoms. Sense of community at T1 partially mediated the link between community safety at T1 and mental health at T2. Higher income and older age were associated with a stronger sense of community, better perceived community safety, and improved health. Policymakers should consider the impact of community factors on well-being during health crises.
American journal of public healthSaahir Shafi, Runhua Xue, Daniel J Mallinson
We examine how political polarization and prolonged crisis governance contribute to narrative numbing in public health emergencies and explore how these dynamics reshape executive emergency powers in the United States. Using Google Trends data, we assess changes in public attention to the opioid epidemic. We follow this with an explanatory case study of Pennsylvania's opioid state of emergency and a comparative review of national legislative reforms to state emergency powers. Prolonged emergency governance during COVID-19 coincided with narrative numbing, weakening the agenda-setting power of emergency declarations. In Pennsylvania, this shift was associated with legislative reforms that constrained executive authority with downstream effects on the opioid emergency. Nationally, state legislatures adopted time-limit, legislative termination, and scope constraints that reallocated authority from executives to legislatures. Narrative numbing is reflected in legislative reforms and has reshaped public health governance by limiting states' capacity to sustain emergency responses to prolonged or recurring public health crises. These changes carry implications for regional health equity and population health outcomes, demonstrating the need to maintain political legitimacy for sustained public health action. (Am J Public Health. 2026;116(11):1719-1726. https://doi.org/10.2105/AJPH.2026.308730).
Dyslexic students faced psychological and educational challenges during the COVID-19 pandemic and online learning, including increased anxiety, low self-esteem, reduced reading interest, limited access to educational technologies, insufficient teacher support, and difficulties with reading fluency and concentration. Examining these challenges is crucial for implementing effective measures and enhancing post-pandemic learning. This study investigates the psycho-educational challenges of dyslexic children during the pandemic, highlighting the need for targeted interventions to support them in current and future contexts. This systematic review identified relevant articles through electronic searches of PubMed, Wiley, Scopus, Web of Science, Google Scholar, and ScienceDirect, supplemented by the snowballing technique, which involved examining the bibliographies of retrieved references. The study identified two main categories of challenges for dyslexic children: psychological (mental health, emotional well-being, behavioural issues, parental stress) and educational (socioeconomic status, technology access, special educational needs, teacher support, remote learning difficulties) affecting children with learning disabilities. The research results show that dyslexic children faced various psychological and educational difficulties identified in this review during the COVID-19 pandemic. Therefore, targeted, evidence-based strategies-such as teacher training, family-school collaboration, adaptive learning technologies, and psychological support-are needed to mitigate these challenges in the post-pandemic period.
Reviews in medical virologyBlanca Taboada, Selene Zárate, Lorena Díaz-González, Juan Manuel Hurtado
Dengue remains a major public health concern in Mexico, with incidence and clinical burden increasing substantially in recent years. Using national surveillance data from 2020 to 2024, this study provides a comprehensive overview of the changing epidemiological landscape, with an emphasis on geographic distribution, temporal trends, serotype dynamics, and disease severity. Over this period, Mexico saw an almost fivefold increase in dengue cases, reaching over 123,000 confirmed infections and 426 deaths in 2024, the highest annual number recorded. Seasonal patterns shifted, with sustained transmission extending into unusual winter months from late 2023. Serotyping data revealed a shift in predominant virus serotypes, with DENV2 predominating until 2022, DENV1 peaking in 2021, and DENV3 rising sharply from 2022 onward, becoming dominant in 2023 and almost exclusive by 2024. This shift coincided with a sustained rise in dengue with warning signs (from 16.9% in 2020 to > 42% in 2023-2024) and higher hospitalisation rates, while severe dengue remained below 5%. Although DENV3 dominated nationally, DENV1 and DENV2 persisted in specific states, and DENV4 circulated sporadically, particularly in southern and northern regions. Several traditionally low-prevalence states experienced atypical outbreaks, underscoring the potential for sudden epidemic expansion. Climatic analysis showed a consistent positive association between temperature and DENV3 prevalence, with precipitation effects varying by year. Odds ratio analysis suggested serotype-specific differences in severity across years. These findings underscore the heterogeneous and dynamic nature of dengue transmission in Mexico and highlight the need for regional surveillance, prevention, and clinical preparedness strategies.
Sexual healthManoji Gunathilake, Jerry L J Chen, Alice Ishwar, Puja Thapa, Roxana Sherry, Natasha Tatipata, Vicki Krause
BACKGROUND: This retrospective study describes the clinical outcomes and management of people diagnosed with syphilis during pregnancy and their newborns at risk of congenital syphilis in the Northern Territory (NT), Australia between 2013 and 2023. METHODS: Demographic, clinical, and contact tracing information on all pregnancies with syphilis diagnosed prior to or during pregnancy, and clinical information of neonates, were sourced from spreadsheets and the NT Syphilis Register Information System. RESULTS: A total of 380 pregnancies were monitored, of which 186 pregnancies were identified as at risk of mother-to-child transmission of syphilis. Reinfection accounted for 13.8% of the 181 new syphilis infections. Of the 188 neonates, there were 11 cases of congenital syphilis, including 1 case of stillbirth. All congenital syphilis cases occurred when maternal syphilis was diagnosed in the third trimester or at the time of childbirth. While maternal treatment was completed in all pregnancies, 22 (11.8%) received treatment less than 30 days prior to childbirth or were untreated at the time of childbirth. Initial treatment was inadequate in 10 pregnancies (5.4%). A lack of four-fold reduction in rapid plasma reagin (RPR) titres by the time of childbirth due to delayed diagnosis and treatment was significantly associated with neonatal congenital syphilis (P < 0.001), with a median RPR of 1:8. Among identified contact/s, 54 (43.2%) tested positive for syphilis. CONCLUSION: Early detection, treatment, and follow-up of maternal syphilis before and during pregnancy are key measures to prevent congenital syphilis. Universal syphilis screening with repeat testing should be incorporated into antenatal care to minimise stigma.
JMIR public health and surveillanceSarah New, Rachel McLean, Robert E Snyder, Beatriz Martínez-López
BACKGROUND: Acute hepatitis C virus outbreaks in California are identified by local health jurisdictions through the investigation of cases reported by laboratories and health care providers to the state's public health surveillance system. However, acute hepatitis C cases are widely underreported, limiting timely outbreak detection and early intervention. SaTScan (Space and Time Scan Statistics) has been proposed as a valuable tool to better detect disease clusters that may be missed by traditional surveillance, even when the disease is underreported, but it is not routinely used for acute hepatitis C surveillance. Timely outbreak detection enables prompt investigation, interruption of transmission networks, and expeditious access to treatment that prevents chronic hepatitis C progression. OBJECTIVE: We assessed the feasibility of using SaTScan to identify verified acute hepatitis C outbreaks using public health surveillance data by conducting a retrospective cluster analysis followed by a prospective, proof-of-concept (POC) analysis that simulated routine surveillance at a single time point using the preceding 2 years of available data. METHODS: We geocoded acute hepatitis C cases with an episode date between January 2022 and December 2023 that were reported to the California Department of Public Health (CDPH). Cases among people experiencing homelessness were included using proxy locations corresponding to their reporting jurisdiction. First, we applied a retrospective space-time permutation scan to determine if any detected significant clusters corresponded to a verified acute hepatitis C outbreak reported in California. We then performed a single prospective POC scan using surveillance data from August 2020 through August 2022 to simulate routine surveillance on August 28, 2022. Detection performance was evaluated based on whether the scan generated a signal corresponding to the known acute hepatitis C outbreak, measured using recurrence intervals. RESULTS: Of the 236 acute hepatitis C cases reported in California with an episode date between January 2022 and December 2023, 97.9% (n=231) were successfully geocoded. The retrospective scan identified 1 significant cluster that corresponded to a verified outbreak in Los Angeles County. The prospective POC scan detected the same outbreak 1 day after the second outbreak-related case was reported, based on symptom onset. The cluster exceeded the recurrence interval threshold (1.7 y), and 2 of 3 outbreak-related cases were identified. CONCLUSIONS: SaTScan successfully identified a verified acute hepatitis C outbreak using both retrospective and prospective space-time permutation scans, demonstrating its potential to enhance real-time surveillance. However, detection performance depends on the timeliness and completeness of case reporting. Future research should explore the prospective use of SaTScan with real-time surveillance data to fine-tune signaling thresholds and scan statistic parameters and assess its broader applicability for acute hepatitis C outbreak detection.
BMJ case reportsJennifer Khong, Alisa Liberman, Arabella Hammoudeh, Karthik Kailasam
A previously healthy woman in her early 30s developed rash, fever and arthralgia 3 weeks after SARS-CoV-2 infection, rapidly progressing to multiorgan failure. Laboratory studies revealed severe thrombocytopenia (23×109/L), microangiopathic haemolytic anaemia, acute kidney injury and ferritin >100 000 ng/mL. Kidney biopsy demonstrated thrombotic microangiopathy with negative antinuclear antibody, supporting atypical haemolytic uraemic syndrome (aHUS). Concurrently, low haptoglobin, elevated lactate dehydrogenase (2500 U/L), interleukin-2 receptor (18 644), triglycerides (425 mg/dL) and splenomegaly supported haemophagocytic lymphohistiocytosis (HLH). Despite plasmapheresis, corticosteroids, etoposide, eculizumab and continuous renal replacement therapy, she died 7 weeks after SARS-CoV-2 infection. Autopsy confirmed aHUS with extensive thrombotic microangiopathy and HLH with bone marrow haemophagocytosis. This case underscores the importance of recognising concurrent aHUS and HLH after COVID-19, as complement-mediated injury and hyperinflammation may produce catastrophic outcomes.
Empirical evidence indicates that societal crises and adverse conditions can negatively impact population mental health. The Big Five personality traits - neuroticism, extraversion, openness, agreeableness, and conscientiousness -significantly influence stress responses. In this article, we examine how personality traits were associated with mental distress during and in the aftermath of the COVID-19 pandemic. Based on data from the Understanding America Study, we find that, since the pandemic began, individuals with high levels of neuroticism were more likely to experience mental distress. By contrast, the remaining personality traits exhibited weaker, inconsistent, or statistically insignificant associations with mental health trajectories. Further analyses indicate that the heightened vulnerability among individuals high in neuroticism was accompanied by elevated risk perceptions, differential adoption of protective behaviors, and less adaptive coping patterns. Taken together, these findings suggest that personality-linked differences, particularly driven by the level of neuroticism, help explain heterogeneity in mental health responses to large-scale societal stressors. Our findings point to the relevance of personality traits (particularly neuroticism) for identifying individuals who may benefit from targeted mental health support during future crises.
Journal of the Royal Society, InterfaceVarun K Rao, Ryan Higgs, Hautahi Kingi, Filippo Radicchi, Santo Fortunato, Maria Litvinova
Human mobility plays a crucial role in the spread of human diseases but is rarely quantified in plant disease epidemics. To address this gap, we integrate a unique, high-resolution network of human movements in New Zealand with a metapopulation model to mechanistically simulate pathogen transmission. We calibrate the model on the nationwide 2010 kiwifruit vine disease (Psa-V) outbreak and show that it reproduces the observed spatio-temporal spread, confirming that the human mobility network is a strong foundation for modelling human-mediated transmission dynamics. By analysing spatial infection trends, we find that most dispersal occurs locally, as often illustrated in the plant-outbreak literature. However, sporadic long-range connections are necessary to model a nationwide outbreak. Using the model as an in silico laboratory, we demonstrate that the severity of human-mediated pathogen transmission is highly sensitive to the timing and location of initial importation. We observe a potential causal link between seasonal labour patterns and epidemic risk in high-traffic seasons. This study showcases a novel data-driven framework for modelling the spatio-temporal spread of agricultural pathogens when human-mediated dispersal is epidemiologically relevant, underscoring the importance of leveraging human mobility networks for building better biosecurity systems.
Environmental monitoring and assessmentMarietta Theodoropoulou, Nikolaos Keramydas, Christina Karatrantou, Eleni Gianni, Taiwo Bolaji, Panagiotis Papazotos
The reduction in human activities during the COVID-19 pandemic, known as the Anthropopause, offers a unique opportunity to evaluate its effects on groundwater, which remains poorly understood. The study aims to evaluate groundwater status during the COVID-19 period in the regional unit (RU) of Messenia, an agricultural area of high tourist interest. Qualitative and quantitative data from borehole investigations were analyzed using an integrated methodological framework. Descriptive statistical analyses, bivariate hydrogeochemical diagrams, geo-environmental indices, and hydrogeochemical evaluations characterized groundwater chemistry and variability, while thematic maps illustrated its spatial patterns. Furthermore, a combined DPSIR-SWOT approach was utilized to systematically assess the groundwater system responses and to evaluate the potential impacts of the Anthropopause on groundwater. The effects of Anthropopause were investigated over five years (2018-2022), allowing for comparison of groundwater characteristics across different phases of human activity (pre- and post-Anthropopause periods). The results showed that elevated EC values and increased concentrations of Cl-, Na+, and NO3- in groundwater are consistent with seawater intrusion and nitrate pollution in Messenia. The data also indicated significant reductions in NO3-, Cl-, and EC values during the Anthropopause, suggesting improved groundwater quality for various uses. In contrast, groundwater conditions deteriorated after tourism increased. The pause in human activities demonstrated significant effects on human-environment interactions, often benefiting natural processes and highlighting the need for effective groundwater resource management. This requires systematic spatiotemporal monitoring of groundwater data to provide insights into the impacts of human activities and climate change.
Current microbiologyAline Madeira Marques Saraiva, Amália Raiana Fonseca Lobato, Emanoele Saraiva Pereira, Maria Paula Cruz Schneider, Diego Assis das Graças, Adonney Allan de Oli…
Acinetobacter baumannii is a high-priority pathogen due to its global dissemination and antimicrobial resistance. This work describes the first report of A. baumannii ST-15 isolates belonging to the International Clone 4 group, that exhibited an MDR profile with the co-production of OXA-23 and OXA-58 enzymes. Strains were isolated from an intensive care unit in a hospital of the Brazilian Amazon. Eight strains were recovered from an intensive care unit, showing high clonal stability across diverse clinical sources, including tracheal aspirates, urine, and blood, which underscores the high versatility and systemic dissemination potential of this lineage.The blaOXA-23 and blaOXA-58 genes were detected in all strains. A. baumannii isolates AB_OXA58_IEC07 and AB_OXA58_IEC02 were selected for hybrid genome sequencing and plasmid reconstruction, respectively, as representative samples of the outbreak. The reconstructed mobilome revealed a genome size of 4,110,050 bp, a GC content of 39.2%, and 3846 coding sequences for the reference strain, while four distinct plasmids were fully resolved.The blaOXA-58 gene was detected flanked by ISAba3 and IS6-like elements.pdif modules were identified in another plasmid, together with mobilization and replication genes. The tet39 gene was also identified in a novel plasmid that is likewise mobilizable. VFDB found several genes related to biofilm formation and virulence. The identification of these high-risk genetic determinants within a monoclonal outbreak, involving diverse clinical sites, emphasizes the successful persistence of the ST-15 lineage in the hospital environment. This study describes a rare co-production of oxacillinases, highlighting the importance of constant genomic surveillance in monitoring the emergence of antibiotic-resistant pathogens that could pose a threat on a regional or global scale.
PloS oneMax Carlos Ramírez-Soto, Hugo Arroyo-Hernandez, Juan Vicente Bogado Machuca, Diego H Stalder, Christian E Schaerer
BACKGROUND: Pneumonia is a leading cause of morbidity and mortality in children and older adults. COVID-19 related disruptions in healthcare and surveillance may have altered incidence, hospitalizations, and deaths. We assessed pneumonia incidence, hospitalizations, and mortality rates in children under five and adults older than 60 years in Peru during the COVID-19 pandemic (2020-22) versus the pre-pandemic period (2015-19). METHODS: We conducted a retrospective population-based time series study using nationwide surveillance system data on reported pneumonia cases, hospitalizations, and deaths in Peru from 2015 to 2022. Age- and region-specific incidence rates (IRs) and incidence rate ratios (IRRs) with 95% confidence intervals were estimated for pneumonia cases, hospitalizations, and deaths by comparing the pandemic period (2020-22) with the pooled pre-pandemic period (2015-19). RESULTS: Between January 1, 2015, and December 31, 2022, 170,558 pneumonia cases were reported among children younger than 5 years and 163,938 among adults aged >60 years in Peru. During the same period, 56,680 and 68,476 hospitalizations and 1,563 and 16,485 deaths occurred in these age groups, respectively. Compared with the pre-pandemic period (2015-2019), pneumonia incidence among children younger than 5 years declined markedly during the pandemic, decreasing by 71% in 2020 (IRR, 0.29; 95% CI, 0.28-0.30), 63% in 2021 (IRR, 0.37; 95% CI, 0.36-0.38), and 12% in 2022 (IRR, 0.88; 95% CI, 0.87-0.90). Hospitalizations and mortality in this group also decreased. In contrast, adults aged >60 years experienced increased hospitalization and mortality rates, particularly in 2021 (hospitalizations: IRR, 2.04; 95% CI, 1.97-2.09; mortality: IRR, 4.28; 95% CI, 4.01-4.57). Substantial regional heterogeneity was observed across Peru. CONCLUSIONS: During the COVID-19 pandemic, pneumonia epidemiology in Peru showed contrasting patterns by age, with sustained declines in incidence, hospitalizations, and mortality among children younger than 5 years, but increased hospitalizations and mortality among adults aged >60 years, underscoring the need to strengthen surveillance, access to timely care, and vaccination programs.
International journal of biometeorologyLe Thanh Trang, Pham Thi Tuyet Huyen, Vo Thi Kim Kieu, Nguyen Thi Van Anh, Le Hong Nga, Hoang Ha Anh, Phan Thi Ha, Nguyen Kim Loi
Dengue fever (DF) remains one of the most significant mosquito-borne diseases in tropical and subtropical regions, particularly in Ho Chi Minh City (HCMC), Vietnam. This study evaluates the performance of Artificial Intelligence (AI) models, including Machine Learning and Deep Learning approaches to forecast weekly district-level DF cases and to identify the optimal predictive model. DF notifications and meteorological data (temperature, humidity, rainfall) from 24 districts in HCMC (2015-2022) were standardized to epidemiological weeks and spatially interpolated using Inverse Distance Weighting (IDW). Variable-specific lags were estimated empirically by Cross-Correlation Analysis (CCA) over 0-21 weeks, and multicollinearity was screened with the Pearson Correlation Coefficient (PCC) and the Variance Inflation Factor (VIF) and resolved with Principal Component Analysis (PCA). Five forecasting models were compared: Multiple Linear Regression (MLR), Support Vector Regression (SVR), Random Forest (RF), Autoregressive Integrated Moving Average (ARIMA), and Long Short-Term Memory (LSTM). Shapley Additive Explanations (SHAP) were applied to assess feature contributions. Strongest lag impacts on DF were found for rainfall (8 weeks), maximum humidity (8 weeks), minimum humidity (8 weeks), minimum temperature (17 weeks), maximum temperature (0 weeks), and temperature amplitude (5 weeks), with correlation |r| ranging from 0.18 to 0.37.Among all models, LSTM achieved the best performance with the lowest errors and highest stability across 2021-2022 test sets. Incorporating lagged meteorological and epidemiological features notably improved predictive accuracy, particularly for MLR. Overall, the LSTM model shows strong potential for dengue forecasting in HCMC and supports the development of AI-based early warning systems for proactive public health management.
No measurement, no understanding; no understanding, no control: this foundational scientific principle was exposed as a public health dysfunction by the COVID-19 pandemic. Transmission chains spread invisibly, and the contact histories, mobility patterns, and biosignals necessary for control were never systematically collected. Although sensors and digital technologies existed, the fundamental reason measurement failed was the absence of privacy infrastructure that would have enabled people to provide data with confidence. This failure had structural reasons. The object of measurement in infectious disease control is not a physical phenomenon but human beings, and measurement therefore enters the core of privacy: contact histories, social relationships, and bodily states. Because greater precision also deepens privacy intrusion, contact-tracing apps faced 2 failures: privacy-centered designs lost epidemiological utility, while utility-centered designs were rejected through public distrust. Neither achieved sufficient measurement. This Viewpoint reframes the problem. Privacy protection is not a constraint that impedes infectious disease control but the enabling condition upon which effective measurement depends. Existing regulations and technical methods have not been designed from this premise and have therefore failed to break the cycle of structural distrust. As an institutional approach to filling this gap, we present VRAIO (verifiable record of AI output), which integrates democratic rule-setting, metadata declaration, third-party verification, tamper-proof ledgers, and violation-deterrence incentives. Once privacy infrastructure is established, this foundational principle can operate freely in infectious disease control for the first time. It will enable high-resolution epidemiology and precision intervention, opening a new path for public health that reconciles infection control with individual autonomy and social freedom without relying on blanket social shutdowns.
Journal of Korean medical scienceEunKyung Nam, Jun Yong Choi, Jung Ho Kim, Young Keun Kim, Sang Il Kim, Dae Won Park, Won Suk Choi, Jin-Soo Lee, Joon Young Song, Boyoung Park, Sunghee Hong, Ky…
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare delivery worldwide, raising concerns about continuity of care for people living with HIV (PLWH). However, its long-term effect on HIV treatment outcomes in resource-rich settings with robust public health infrastructure remains unclear. Therefore, this study aims to evaluate the effects of the COVID-19 pandemic on virological outcomes, immunological status, healthcare utilization, medication adherence, and mortality among PLWH enrolled in the Korea HIV/AIDS Cohort. METHODS: A retrospective longitudinal analysis was conducted using the Korea HIV/AIDS Cohort data collected between 2018 and 2023. Outcomes during the pre-pandemic (2018-2019) and pandemic (2020-2023) periods were compared. The primary outcome was virological failure, defined as an HIV RNA level ≥ 200 copies/mL. Secondary outcomes included CD4+ T-cell count, opportunistic infections, visit adherence (≥ 2 clinic visits/year), all-cause mortality, and visual analog scale-assessed self-reported medication adherence. Repeated-measures analyses were performed using generalized estimating equations with an exchangeable correlation structure, adjusted for age and sex. Mortality risk was evaluated using Cox proportional hazards models, with subgroup and sensitivity analyses also performed. RESULTS: Overall, 1,674 patients contributed 9,721 visits. Virological failure decreased from 3.2% pre-pandemic to 1.2% during the pandemic (adjusted odds ratio [OR], 0.37; 95% confidence interval [CI], 0.27-0.50; P < 0.001). CD4+ T-cell counts were higher during the pandemic (β = +33.2 cells/mm³; 95% CI, 23.3-43.1; P < 0.001). Medication adherence improved from 85.3% to 90.2% (adjusted OR, 1.58; P < 0.001), despite reduced visit adherence (81.6% to 60.5%; adjusted OR, 0.49; 95% CI, 0.45-0.54; P < 0.001). All-cause mortality did not differ between periods (hazard ratio, 0.32; 95% CI, 0.07-1.51; P = 0.151), with consistent findings across subgroup and sensitivity analyses. CONCLUSION: Despite reduced clinic utilization during the COVID-19 pandemic, PLWH in Korea maintained or improved virological and immunological outcomes. These observational findings support the feasibility of less intensive monitoring for selected virologically stable individuals. However, given the potential for survivorship bias and unmeasured confounding, prospective studies are required before changes to monitoring practice can be recommended.
Primary health care research & developmentCaner Vizdiklar, Volkan Aydin, Gokhan Tazegul, Ahmet Akici
AIM: We aimed to examine changes in antidiabetic drug utilization associated with implementation and subsequent easing of pandemic-related restrictions. BACKGROUND: The COVID-19 pandemic and associated restrictions disrupted healthcare access and glycemic regulation, affecting diabetes management. METHODS: We collected nationwide outpatient antidiabetic drug sales and projected prescribing data from IQVIA Turkey between 01.03.2018 and 31.12.2022. We assessed average monthly consumption, expenditure, and quarterly prescribing trends across 'before restrictions' (BfR, 01.03.2018-31.03.2020), 'during restrictions' (DuR, 01.04.2020-31.03.2022), and 'after restrictions' (AfR, 01.04.2022-31.12.2022) periods. Consumption and prescribing levels were expressed as 'defined daily doses/1,000 inhabitants/day' (DID). RESULTS: Antidiabetic consumption increased from 123.6 ± 12.2 DID in BfR to 156.3 ± 25.4 DID in DuR and remained elevated in AfR (151.2 ± 28.9 DID), paralleled by expenditure (€63.6 m ± 8.4 m, €85.1 m ± 14.8 m, and €83.9 m ± 19.1 m, respectively). Prescribing levels declined from BfR to DuR (56.4 ± 3.5 to 29.9 ± 3.6 DID, p < 0.001) and slightly recovered in AfR (46.0 ± 10.9 DID, p > 0.05 vs. earlier periods). Oral antidiabetic consumption rose from 71.2 ± 6.8 DID in BfR to 90.6 ± 17.2 DID in DuR (p < 0.001) and further to 96.9 ± 19.4 DID in AfR (p < 0.001 vs. BfR), while sodium-glucose cotransporter-2 inhibitor use increased across periods (p < 0.001). Injectable antidiabetic consumption, mainly insulins, increased from BfR to DuR (p < 0.001), and decreased in AfR (p < 0.01 vs. DuR). CONCLUSION: We demonstrated a sustained increase in antidiabetic consumption following implementation of COVID-19-related restrictions, persisting beyond easing of most measures. Medication-access policies, panic stockpiling, improved glycemic adherence, and newer therapies might have contributed. These findings may inform strategies to strengthen family physician-community pharmacist coordination while maintaining treatment continuity and optimizing medication access during future public health emergencies.
BACKGROUND: COVID-19 negatively impacted cancer diagnostic and treatment services worldwide. These challenges were further compounded in low- and middle-income countries, where longstanding resource constraints limited the capacity to maintain standard treatment pathways. We aimed to assess the impact of COVID-19 on (i) stage at diagnosis and time intervals from symptom recognition to a pathological confirmed breast cancer (BC) diagnosis and (ii) treatment initiation at two academic hospitals in Johannesburg; Chris Hani Baragwaneth Academic Hospital (Site 1) and Charlotte Maxeke Johannesburg Academic Hospital (Site 2). METHODS: We compared the proportion of BC cases diagnosed at a late stage (stage III/IV) and median time intervals of pre-contact (T1), diagnostic (T2) and treatment initiation following diagnosis (T3) pre, during and post COVID-19 among 2522 women. Using cumulative Kaplan-Meier time-to-event analysis we assessed the proportions of women achieving internationally benchmarked intervals. RESULTS: Late-stage BC diagnoses increased during COVID-19 but subsequently recovered, with pre-, during-; and post-COVID-19 percentages, respectively, of 50%, 60% and 53% at Site 1 and 63%, 69% and 55% at Site 2. Compared to pre-COVID-19, at Site 1 the T1 interval increased during and post COVID-19 (from 0.8 (IQR: 0.3-4.0) months to 1.0 (IQR: 0.5-6.0) and 2.0 (IQR: 0.5-6.0) post COVID-19 (P < 0.001), respectively); there were no significant T1 changes at Site 2. Delays more than 3 months were associated with late-stage diagnosis. T2 intervals did not differ significantly across COVID-19 periods at both sites. The treatment interval (T3) at Site 1increased from a pre-COVID-19 median of 1.6 (IQR: 1.0-2.6) to 2.0 (IQR: 1.2-4.3) during COVID-19 and remained at 2.0 (IQR: 1.1-4.0) post COVID-19 (P < 0.001); at Site 2 an increase also occurred during COVID-19 but was not significant. Internationally benchmarked staging and timeliness targets were never achieved. CONCLUSIONS: The already high prevalence of late-stage at diagnosis increased further during the COVID-19 pandemic with evidence of recovery at both sites in the post COVID-19 period. Treatment initiation delays increased and surgery volumes decreased during the pandemic and did not recover to pre-pandemic levels. Our study shows current cancer human and facility resources are insufficient to manage the steadily increasing BC burden in Johannesburg, South Africa.
BACKGROUND: The ready-made garments (RMG) industry is a crucial component of Bangladesh's economy, using over 4 million workers from low-income backgrounds who often neglect their health care needs. Historically, this sector has faced criticism for labor exploitation, unsafe working conditions, and rights violations, as highlighted by tragic accidents resulting in loss of life. Compliant factories may uphold higher labor standards, but many noncompliant factories expose workers to poor conditions, increasing health risks. The COVID-19 pandemic intensified vulnerabilities, leading to widespread factory closures and job losses, increased health risks, and left millions of workers without wages. Although the government attempted to provide some relief, it fell short in offering job security, social protection, health services, and emergency assistance. Limited access to technology due to digital literacy gaps further hinders these workers, who primarily use basic mobile phones for communication rather than accessing health or emergency services. Thus, there is a pressing need to develop a sustainable system that capitalizes on their existing technological familiarity. OBJECTIVE: Our goal was to gain a deep understanding of RMG workers' experiences, focusing on their work environments, technological interactions related to health care management, and the impacts of COVID-19 on their circumstances. This understanding aims to inform the design of a technology-based framework that is both sustainable and contextual. METHODS: In phase 1, we conducted in-person interviews with 55 RMG workers, comprising 32 female and 23 male participants from urban and suburban areas of Dhaka and Gazipur, before the pandemic. Participants were aged between 18 and 40 years. In phase 2, we reconnect with 12 phase 1 participants during the pandemic and also consulted 3 stakeholders from RMG factories via phone. Each interview, conducted in Bengali, was recorded with consent, totaling 846 minutes of discussion that were translated and transcribed. Thematic analysis was used to analyze the results. RESULTS: Insights gathered revealed variations in working conditions, personal experiences, perceptions of health care, lifestyle choices, and technology use tied to factory compliance. Workers at compliant factories had better health care support and used technology more effectively than those in noncompliant settings. The pandemic drastically altered the landscape for all workers, heightening health and safety concerns and shortages of emergency assistance. The RMG sector faces significant challenges, highlighting the urgent need for targeted emergency relief and health services. CONCLUSIONS: This research examined the challenges and technology use among RMG workers during the pandemic, with a focus on health care perspectives. Based on our findings, we proposed a technology-based framework called VOICE (Virtual Outlet for Integrated Community Engagement) that connects workers with service providers through a simplified interface. This aims to assist marginalized communities during emergencies and enhance their overall well-being.
Preventive oral health care and education are essential for soldiers' health and military readiness. This study investigated oral health behaviors, dental service utilization, oral health perceptions, and educational needs among enlisted South Korean Army soldiers during the coronavirus disease 2019 pandemic. A cross-sectional survey was conducted among 313 enlisted soldiers who visited military dental clinics in Gyeonggi-do, Republic of Korea, from March 24 to April 16, 2021. Descriptive statistics and Pearson's χ2 tests were performed. Overall, 60.4% of participants did not use oral care products, mainly because they did not perceive a need for them (62.9%). Furthermore, 71.9% had not undergone routine dental examinations, 63.6% had not received dental treatment after enlistment, and 91.4% had no oral health education experience during military service. Video-based education was the preferred method (40.6%), and halitosis prevention and management was the most preferred topic (20.4%). Preferred educational methods did not differ significantly according to age, military rank, educational level, or smoking status (all P > .05). Military rank was significantly associated with perceived adequacy of oral care time (P < .001) and the place of dental treatment (P = .048). Routine dental examinations, dental treatment experience, and oral health education experience showed no significant differences according to participants' general characteristics. Preventive oral health services and education were insufficient among enlisted South Korean Army soldiers. Tailored programs reflecting soldiers' needs and preferred learning methods should be developed and evaluated.
MedicineŞahin Temel, Serap Şahin Ergül, Ali Yeşiltepe, Recep Civan Yüksel, Ahmet Safa Kaynar, Murat Sungur, Kürşat Gündoğan
Adipokines regulate metabolic and inflammatory pathways and may be altered during critical illness. We explored sequential serum adipokine concentrations and their associations with nutritional and clinical variables in critically ill COVID-19 patients. This prospective observational, exploratory study included 30 critically ill COVID-19 patients and 10 age- and sex-matched healthy controls. Serum adiponectin, resistin, GLP-1, visfatin, IGF-1, leptin, and acylated ghrelin were measured at intensive care unit admission and on day 7. Biomarker-clinical correlations were analyzed using Spearman correlation, and the Benjamini-Hochberg false discovery rate procedure was applied to account for multiple biomarker comparisons. After false discovery rate correction, longer time to nutrition initiation remained inversely associated with day-7 adiponectin (ρ = -0.464, q = 0.027), GLP-1 (ρ = -0.568, q = 0.015), IGF-1 (ρ = -0.488, q = 0.022), leptin (ρ = -0.539, q = 0.015), and acylated ghrelin (ρ = -0.503, q = 0.021). Several adipokines showed exploratory associations with nutrition-initiation time in this small cohort of critically ill COVID-19 patients. These observational findings do not establish that earlier nutritional support causes changes in adipokine concentrations and require validation in larger, adequately controlled studies.
Emerging infectious diseasesElla F Madden, Sally L Ellis, Andrea Parisi, Christine E Selvey, Janaki Amin
We compared data from the 2015 and 2024 pertussis epidemics in New South Wales, Australia. In 2024, we found twice as many notifications and a shift in distribution to older children. COVID-19 interventions and lack of circulation of pertussis likely contributed to an age cohort immunity gap and increased infections.
INTRODUCTION: Women working as informal food vendors in Kisumu faced precarious work conditions that worsened during the COVID-19 pandemic. Despite playing a vital role in urban household food security, they were excluded from policy decisions, which were largely confined to technical experts and national government officials. METHODS: Using the Intersectionality-Based Policy Analysis (IBPA) framework, this study examined the engagement of women informal food vendors and the disparities in COVID-19 control policies. Between July 10, 2024, and October 15, 2024, we conducted a qualitative study using key informant interviews (n = 20), in-depth interviews (n = 20), four focus group discussions (n = 40; 10 participants each), and a purposive review of four policy documents. Participants were recruited via purposive sampling in collaboration with Pamoja Community Based Organisation, and data were analyzed thematically guided by the IBPA principles. RESULTS: The findings indicate that excluding women vendors from decision-making led to gender-insensitive policies that worsened existing inequalities by overlooking the vendors' diverse social identities. Furthermore, inconsistent policy implementation increased gender-based vulnerabilities, leaving these women exposed to harassment, extortion, and physical assault. DISCUSSION: To prepare for future emergencies, governments must establish inclusive, gender-responsive policy frameworks that prioritize the perspectives of informal food vendors, thereby safeguarding sustainable urban food systems. Specifically, municipal, county, and national authorities should create consultative mechanisms to ensure women informal food vendors actively participate in decision-making processes. Such integration will foster gender-sensitive policy development and keep vendors' lived experiences central to urban food governance. Ultimately, this research demonstrates the value of applying an intersectional policy analysis framework to health research, advancing equity and social justice by strengthening the participation of marginalized groups in emergency response and regulatory planning.
PloS oneMorteza Babazadeh Shareh, Florian Kleiner, Michael Böhme, Corinna Hägele, Petra Dickmann, Rainer Heintzmann
The COVID-19 pandemic presented severe challenges in understanding and predicting the spread of infectious diseases, necessitating innovative approaches beyond traditional epidemiological models. This study introduces an advanced method for automated model discovery using the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm, leveraging a dataset from the COVID-19 outbreak in Thuringia, Germany, encompassing more than 400,000 patient records and vaccination data. We develop a flexible, data-driven model capturing pandemic dynamics, incorporating external factors and interventions into the mathematical framework. The fixed coefficient values globally determined by SINDy were not accurate for local modelling of the data, a limitation of prior SINDy-based epidemiological applications that our framework directly addresses. We therefore refined our technique based on the differential equations as found by SINDy, by investigating three modifications that account for recent local data, each offering different strengths for short-term prediction, scenario analysis, and capturing nonlinear effects, achieving an R² of 0.87 at a one-week horizon. In a first approach, we re-optimized the coefficient values using seven days of past data, without changing the globally determined differential equation. In a second approach, we allowed a temporal dependence of the coefficient values, fitted using all previous data, in combination with regularization. As a last method, we kept the coefficients fixed to the original values but augmented the differential equation with a small neural network, locally optimized to the data of the past week. Our results link vaccination and public health measures to the pandemic's trajectory. The proposed model allows simulation of intervention scenarios, such as vaccination strategies and public health interventions. While the current study is based on retrospective data from a single region, the framework could serve as a basis for exploring responses to future outbreaks, subject to further validation.
Journal of medical virologyYu Chen, Meng Shang, Shengping Dou, Xiaoxu Wang, Haoqiang Ji, Qiyong Liu
BACKGROUND: Dengue remains a major mosquito-borne disease in China. The COVID-19 pandemic and associated non-pharmaceutical interventions (NPIs) profoundly altered human mobility and public health responses, potentially reshaping dengue transmission dynamics. However, comprehensive nationwide evidence on their long-term epidemiological impact is limited. OBJECTIVE: This study aimed to evaluate changes in dengue epidemiology in China before, during, and after the COVID-19 pandemic, with a focus on temporal periodicity, importation and indigenous transmission, counterfactual deviations from pre-pandemic trends, and spatial risk redistribution. METHODS: We conducted a nationwide retrospective spatiotemporal study using reported dengue cases in China from 2015 to 2024. Epidemiological characteristics were compared across pre-pandemic, pandemic, and post-pandemic phases. Morlet wavelet analysis was used to assess temporal periodicity. A SARIMA model fitted to pre-pandemic data generated counterfactual forecasts for 2020-2024. Spatial patterns were evaluated using provincial incidence mapping, Global Moran's I, and Local Indicators of Spatial Association. RESULTS: A total of 87 182 dengue cases were reported, with major peaks in 2019 and 2024. Imported cases declined sharply during 2020-2022 and rebounded after 2023, whereas indigenous transmission became increasingly dominant. Annual periodicity weakened during the pandemic but re-emerged after 2023. Observed incidence during 2020-2022 was frequently below counterfactual expectations, while substantial positive deviations appeared from mid-2023 and intensified in 2024. Post-pandemic dengue risk re-emerged in South and Southwest China and expanded inland, with weaker provincial clustering. CONCLUSIONS: COVID-19 and related NPIs substantially reshaped dengue epidemiology in China, suppressing transmission during 2020-2022 but followed by a marked post-pandemic resurgence, increasing indigenous transmission, disrupted but re-emerging seasonality, and broader inland spread.
Chaos (Woodbury, N.Y.)Jian Wang, Haixiao Wang, Wei Shao, Jie Chen, Shanshan Ge, Junseok Kim
This paper uses a network model to analyze the impact of the COVID-19 pandemic on global trade centers. Using import-export trade data from 12 major economies, we visually assess the shifts in global trade network positions before and after the pandemic. By constructing a balanced trade network for the years 2018, 2019, and 2020, we examine how the pandemic has affected the trade connections of key countries. Our study finds that China maintained positive growth and strengthened its trade ties with the United States, while other major economies experienced declines in their network positions. Subsequently, we apply Liang-Kleeman Information Flow to conduct a causal analysis of the past 30 years of gross domestic product and trade data between China and the United States, demonstrating how economic growth patterns influence changes in the global trade network. This combination of network analysis and causal inference provides robust support for our conclusions on the evolving structure of global trade centers.
Emerging infectious diseasesBakhodir B Rakhimov, Laziz N Tuychiev, Nilufar T Khamzayeva, Nigora U Tadjiyeva, Nargiza S Saidkasimova, Nargiza X Otamuratova, Xolmamat N Norboev
Tashkent, Uzbekistan, registered 290 invasive meningococcal disease cases during January-April 2026; the case fatality rate was 8.3%. Meningeal signs appeared in only 3.1% of patients and were the sole signs associated with death. Neisseria meningitidis serogroup surveillance and conjugate vaccine introduction will be needed to prevent invasive meningococcal disease in Uzbekistan.
Emerging infectious diseasesKursat Altay, Nazif Elaldi, Ufuk Erol, Binnur Koksal, Omer Faruk Sahin, Ayse Nur Pektas, Seyit Ali Buyuktuna, Murtaza Oz, Yasemin Cakır Kıymaz, Tuba Nur Tasset…
Anaplasma capra is a recently discovered bacterial tickborne pathogen that was first identified in goats in 2012 and later in humans in China in 2015. We detected and genetically characterized A. capra in adult patients with suspected Crimean-Congo hemorrhagic fever (CCHF) in Turkey during the 2022 outbreak. We screened all patients for A. capra by using nested PCR targeting the gltA and groEL genes. We confirmed CCHF by molecular and serological tests. Of 263 patients, 6 (2.28%) were positive for A. capra. Sequence analysis revealed 84.16%-100% gltA gene similarity and 90.24%-100% groEL gene similarity with GenBank entries. Phylogenetic analysis confirmed all A. capra gene sequences belonged to genotype 1. Our results demonstrate clinical evidence of genotype 1 A. capra infection in humans. Our findings highlight the need for clinicians to consider A. capra in the differential diagnosis of CCHF-like symptoms, especially in endemic areas.
Emerging infectious diseasesSuzanna M Storms, Jade Rathmann, Lynette Hemker, Miranda Vieson, Leyi Wang
In 2025, highly pathogenic avian influenza A(H5N1) virus was detected in a poultry flock in Illinois, USA. Quantitative reverse transcription PCR, sequencing, and histopathology on cat and rat samples from the farm showed multiple positive tissues and high sequence identity to an avian isolate. Small mammals might contribute to H5N1 transmission.
MicrobiologyOpenPatrick Forstner, Christine Uitz, Johanna Dabernig-Heinz, Gabriel E Wagner, Jennifer Bender, Martin Fischer, David Siebenhofer, Guido Werner, Tobias Busche, Le…
A significant increase of vancomycin-resistant Enterococcus faecium (VREfm) infections was observed in South-Eastern Austria since 2024. The prolonged outbreak is caused by a novel vanB-VREfm clone (ST117/CT7799, "VREfmstyr"). This study characterizes the atypical difficult-to-detect resistance phenotype and assesses the genomic relatedness of the isolates. Patient and outbreak characteristics were investigated including whole genome sequencing of the isolates. Sensitivity of broth microdilution (BMD), gradient tests (GT), disk diffusion (DD), and automated susceptibility testing (VITEK2) was compared. The performance of commercial screening media was evaluated. From sporadic detections in early 2024 case numbers began to rise during the year. In 30/31 (97%) of all cases, intra-hospital transmission was considered likely and an association with invasive procedures was identified in most cases. Core genome multilocus sequence typing revealed only six allelic differences between VREfmstyr isolates collected in a 12-month period, all belonging to the E. faecium ST117/CT7799 lineage. BMD detected vancomycin resistance (MIC > 4 mg/L) in no more than 16/31 (52%) of isolates after 24 h incubation, while GT and DD misclassified all isolates. Only prolonged incubation improved the performance of these assays. VITEK2 analysis, however, correctly classified all 31 isolates. Of four commercially available VRE-screening agars, only one was capable of detecting VREfmstyr after 24 h incubation. The emergence and clonal dissemination of VREfm ST117/CT7799 reveals a serious diagnostic gap as commonly used diagnostic algorithms fail to reliably detect this resistance phenotype. Our findings should help to further evaluate the true geographical distribution and clinical significance of this novel VREfm clone.
Emerging infectious diseasesEduardo Juscamayta-López, Faviola Valdivia, Carmen Rodríguez-Cueva, Helen Horna, Yaneth Quispe, María Pía Soto, Segundo Torres, Victor Fiestas Solórzano, Marti…
We report the emergence of macrolide-resistant Bordetella pertussis during a pertussis outbreak in Peru. Among 68 cases, 31% carried the A2047G gene mutation, conferring resistance to macrolides. Whole-genome sequencing revealed 2 genetically distinct groups, indicating multiple introductions into Peru. Our findings support strengthening surveillance for macrolide-resistant pertussis to inform control strategies.
Developmental psychologyJennifer G Bohanek, Diana Leyva, Ashley M Groh
In March of 2020, the lives of billions of people changed. The COVID-19 pandemic was unique as it was an extended event-without a clear end-that involved lockdowns, quarantines, and restrictions, but it was also a time when many parents and children spent large amounts of time together at home sheltering in place. In this special issue, we bring together research from diverse populations across the globe centered on family conversations about the COVID-19 pandemic. The research presented here showcases the breadth of research methods dedicated to family communication, spans developmental periods ranging from early childhood through adolescence, incorporates different constellations of family members, was collected at multiple time points across the pandemic, and examines the mechanistic role that familial conversations may have for child and family well-being. This work has important implications and applications for future widespread societal challenges and, taken together, provides compelling evidence that one way forward may be to focus efforts on resource-efficient and easy-to-implement interventions that target changes in family communication patterns prior to, during, and/or after significant life events. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Emerging infectious diseasesLingzi Xiaoli, Taylor Griswold, G Sean Stapleton, Lee S Katz, Zachary Ellison, Kaitlin A Tagg, Hattie E Webb, Katharine Benedict, Jessica C Chen
Nontyphoidal Salmonella enterica serovar Hadar causes poultry-associated salmonellosis outbreaks in the United States. One persisting strain of Salmonella Hadar caused 5 multistate outbreaks resulting in ≈2,000 human cases during 2020-2023. The Centers for Disease Control and Prevention designated the strain as reoccurring, emerging, or persisting (REP), related within 26 core-genome allele differences. That REP strain has caused human illnesses by consumption of commercial poultry food products or contact with backyard poultry. To investigate the REP strain's evolution and identify possible markers for source attribution, we performed phylogenetics and molecular clock analysis on 404 genomes subsampled from routine surveillance and outbreaks. The most recent common ancestor likely emerged in early 2018. We identified 2 clades: clade 1, associated with backyard poultry and other food sources, and clade 2, predominantly linked to commercial poultry products. We found 2 clade-specific single-nucleotide polymorphism markers; in silico screening of additional isolates supported their use for source attribution.
Emerging infectious diseasesJianxu Zhang, Peng Lv, Teng Zhao, Hanji Jiang, James S Squire, Martin S Yonnie, Zikan Koroma, Ibrahim F Kamara, Abdulai A Jalloh, Guangqian Pei, Yunfei Wang, H…
We report a cutaneous ulcer outbreak in Sierra Leone in 2025 that predominantly affected ≈403 schoolchildren. The causative agent was confirmed as Haemophilus ducreyi, a bacterium traditionally associated with the sexually transmitted infection chancroid but more recently recognized as an emerging cause of lower limb cutaneous ulcers in tropical regions.
Yonsei medical journalAh Young Leem, Shihwan Chang, Mindong Sung, Chanho Lee, Kyung Soo Chung, Young Sam Kim, Sunghoon Park, Onyu Park, Taehwa Kim, Hye Ju Yeo, Jin Ho Jang, Woo Hyun…
PURPOSE: Coronavirus disease 2019 (COVID-19) increases the risk of bloodstream infections (BSI), but associated risk factors remain incompletely characterized. We aimed to evaluate BSI risk factors in patients admitted to the intensive care unit for COVID-19. MATERIALS AND METHODS: This nationwide multicenter study, conducted across 22 university-affiliated hospitals in South Korea, included COVID-19 patients treated with high-flow nasal cannula (HFNC) therapy or mechanical ventilation. Baseline characteristics were compared between patients who developed BSI within 30 days and those who did not. Pathogens were analyzed, risk factors were evaluated using multivariable logistic regression, and supplementary Cox proportional hazards analyses were performed to address time-dependent outcomes. RESULTS: Of 573 included patients, 206 (35.9%) developed at least one BSI episode. Staphylococcus species were the most frequent isolates. Gram-negative bacteria became increasingly prevalent over time, while fungal infections were associated with prolonged hospitalization. Multivariable analysis identified chronic neurological disease, higher baseline Sequential Organ Failure Assessment score, mechanical ventilation, prone positioning, and extracorporeal membrane oxygenation (ECMO) use prior to infection as independent BSI predictors. Notably, although crude in-hospital mortality was significantly higher in the BSI group (41.5% vs. 31.7%, p=0.012), BSI was not an independent predictor of in-hospital mortality in either logistic regression or Cox analyses. CONCLUSION: In critically ill patients with COVID-19, high baseline severity, chronic neurological disease, and pre-infection advanced life support (mechanical ventilation and ECMO) were independent predictors of BSI. Rather than acting as an independent cause of death, BSI primarily serves as a clinical marker of extreme illness severity and prolonged invasive interventions.
Disease now-casting increasingly relies on non-traditional data, such as online activity, which offer fast, inexpensive insights but are often noisy, unstructured, and influenced by behavioral confounders. Models using search engine data have frequently suffered from overfitting and unstable performance. However, pandemics may help distinguish true disease signals from behavioral noise, as both tend to surge during outbreaks. We propose a hybrid approach to improve prediction that combines model evaluation with behavioral insight. We apply simple supervised and unsupervised methods to different flu and COVID-19 datasets, using the 2009 H1N1 and 2020 COVID-19 pandemics as training periods. In both cases, selecting a curated subset of search terms improved model performance, reduced overfitting, and increased stability, consistently outperforming models that used search terms indiscriminately. These results suggest that feature curation informed by behavioral insights can enhance now-casting beyond purely statistical approaches. Our method offers a scalable and adaptable framework for integrating digital epidemiology into public health surveillance.
Influenza and other respiratory virusesNiko Tervo, Marjaana Pitkäpaasi, Pilvi Hepo-Oja, Hanna Jarva, Anna Katz, Erika Lindh, Richard Lundell, Minna Paloniemi, Laura Savolainen, Carita Savolainen-Kop…
BACKGROUND: In 2024, a severe outbreak caused by human adenovirus type 7d (HAdV-7) occurred in Finnish military garrisons. Molecular typing was implemented to support outbreak control. The aim of this study was to determine adenovirus types circulating in Finnish garrisons during 2013-2023 by retrospective surveillance and to review earlier findings to better understand factors contributing to the 2024 outbreak. METHODS: Adenovirus-positive respiratory samples collected through routine surveillance (2013-2023) and enhanced surveillance (2024-2025) were typed using type-specific PCR assays targeting types 3, 4, 7, 11, 14, 16, and 21. Whole-genome sequencing was performed on 11 selected samples. Index case interviews were conducted among conscripts infected with HAdV-7 in late 2023. RESULTS: During 2013-2023, among 497 typed samples, HAdV-4 was most common (n = 446; 89.7%), followed by HAdV-3 (n = 25; 5%). Other types detected were HAdV-21 (n = 11; 2.2%), HAdV-7 (n = 6; 1.2%), and HAdV-11 (n = 1; 0.2%). HAdV-4 was predominant in 2013-2017 and HAdV-3 in 2018-2019. Between February 2024 and June 2025, 1692 adenovirus-positive respiratory samples were typed. The adenovirus types detected were HAdV-4 (n = 1133; 67%), HAdV-7 (n = 440; 26%), co-detection of HAdV-4 and -7 (n = 70; 4.1%), and HAdV-14 (n = 1; 0.1%). Epidemiological investigation and whole-genome sequencing data revealed that the adenovirus associated with the 2024 outbreak (HAdV-7d) was already circulating in Finnish garrisons in 2023. CONCLUSION: The severity of the 2024 outbreak may reflect limited prior circulation of HAdV-7 in Finland. Although HAdV-7 continued to circulate among conscripts in 2025, the severity of the epidemic subsided, possibly due to effective preventative measures guided by active surveillance.
Emerging infectious diseasesMichaella Jaba, Emmanuel Saidu, Emmanuel S Kamanda, Christina Frederick, Laurens Liesenborghs, Megan Halbrook, Nicole A Hoff, Placide Mbala-Kingebeni, Isaac I …
During the 2025 mpox outbreak in Sierra Leone, we assessed environmental contamination in 2 hospitals. Of 89 surfaces sampled, 6 (6.7%) surface samples, primarily from doors, were PCR-positive for monkeypox virus. Our findings highlight monkeypox virus surface contamination in healthcare settings and help prioritize infection prevention and control targets in resource-limited settings.
Prehospital and disaster medicineAileen M Marty, Christian K Beÿ, Kristi L Koenig
The Andes Virus (ANDV) outbreak reported on May 2, 2026, aboard a luxury vessel departing from Ushuaia, Patagonia, Argentina, was caused by an Orthohantavirus unique in its person-to-person transmissibility in contrast to zoonotic transmission characteristic of better-known hantaviruses. Containment required coordinated international management because passengers and crew embarked and disembarked at several international ports-of-call prior to outbreak recognition, resulting in cross-border transmission potential. Among those who disembarked, several traveled on flights to various destinations. Cases subsequently manifested in multiple countries, including Tristan da Cunha, Spain, France, Switzerland, South Africa, Canada, and The Netherlands. Upon notification, international health authorities implemented containment measures, such as contact tracing, quarantine, and isolation. Uniquely, ANDV poses distinctive risks due to its immediately prodromal presymptomatic transmission potential, initial non-specific flu-like symptoms, prolonged incubation period, conceivable long-term neurologic and endocrinologic sequalae, high case fatality rates (CFRs), and possibility of international dissemination. This report describes the successful management of a multi-national outbreak associated with cruise-ship travel, a setting with unique challenges. It also examines implications and challenges for prehospital, health care facility, and public health systems for future ANDV outbreaks. The event was characterized by delayed recognition, international spread, and complex coordination across multiple jurisdictions and sectors, including medical and public health authorities, policy- and decision-makers, crisis and emergency risk-communication experts, media, logistics, transportation, and security. Rapid implementation of public health measures coupled with clinician implementation of the Identify-Isolate-Inform (3I) model, a clinical framework to detect and prevent the spread of infectious disease, at the prehospital and health care facility levels are critical actions that can contain future ANDV outbreaks.