Weizhong Yang

Background:The global epidemiology of mpox has changed substantially since its first documented human case in 1970, particularly following the multinational clade IIb outbreak in 2022 and the emergence of clade Ib since late 2023. However, temporal, regional, and clade-specific changes in the global disease burden of mpox remain incompletely characterized.Methods:We systematically searched Scopus, Web of Science, and Embase for studies published from 1970 to October 11, 2025, reporting mpox incidence, hospitalization, or case fatality, supplemented by relevant WHO reports. Meta-analysis and mixed-effects models were used to quantify disease burden and explore potential influencing factors. WHO surveillance data through November 14, 2025, were additionally analyzed to characterize temporal and regional trends.Results:Seventy studies published between 1970 and 2025 were included. Hospitalization and case-fatality rates declined from 33% and 3.3% before 2022 to 10% and 0.7% during the clade IIb–dominated global outbreak, respectively. However, clade Ia infections remained substantially more severe, with hospitalization and case-fatality rates of approximately 80% and 9%, respectively. Since 2024, Central Africa has again become a major contributor to global mpox cases and deaths, whereas high-income regions experienced larger but clinically milder outbreaks. Overall, despite global declines in disease severity, the burden of mpox remained disproportionately concentrated in Africa.Conclusions:The global burden of mpox is characterized by substantial temporal, regional, and clade-specific heterogeneity, with severe disease remaining concentrated in Africa, particularly Central Africa. Strengthened clade-specific surveillance, targeted vaccination, and enhanced health-system capacity are urgently needed in endemic regions. Future One Health approaches integrating human, animal, and environmental surveillance will be essential to improve preparedness for emerging mpox lineages and mitigate the continuing global burden of mpox.

Background: Digital technologies increasingly shape responses to acute respiratory infection (ARI) symptoms through information seeking, consultation, medication purchase, monitoring, and access to diagnostic products or services. However, how digital health engagement overlaps with in-person facility attendance and whether digital and other out-of-facility behaviors provide complementary signals for episodes that are less visible in routine facility-based surveillance remain unclear. Objective: This study estimates the distribution of ARI episodes by in-person facility attendance and digital health engagement, describes digital and nondigital out-of-facility actions and the reported ordering of these actions, and examines subgroup differences. Methods: We conducted a population-based cross-sectional survey in 11 Chinese cities using multistage stratified random sampling. Participants reported ARI symptoms within the preceding 14 days and subsequent health-related actions. The primary digital composite included online health information seeking, AI-assisted consultation, telemedicine, online medication purchase, wearable device–based self-monitoring, digitally accessed self-administered rapid antigen testing, and at-home pathogen specimen collection. Participants were cross-classified by in-person facility attendance and digital health engagement. Weighted descriptive proportions were estimated using poststratification weights, with 95% CIs calculated using Wilson score intervals based on the Kish effective sample size. Behavioral sequences were descriptively reconstructed from retrospectively reported timing of actions using 1 representative action per reported day, with adjacent-transition CIs estimated by participant-level bootstrap resampling. Modified Poisson regression with individual-level robust variance estimation was used to estimate adjusted associations with in-person facility attendance, expressed as adjusted prevalence ratios (aPRs). Results: Among 247,530 participants, 68,650 reported ARI symptoms. Among symptomatic participants, 19.18% (95% CI 18.87%-19.48%) reported in-person facility attendance, and 18.94% (95% CI 18.64%-19.24%) reported at least one digital health behavior. Digital health engagement without in-person facility attendance comprised 11.20% (95% CI 10.95%-11.44%) of ARI episodes, while 7.74% (95% CI 7.54%-7.95%) involved both dimensions. Digital health engagement was positively associated with in-person facility attendance during the same episode (aPR 2.12, 95% CI 2.05-2.20). Compared with participants reporting 2 or fewer symptoms, the aPRs were 3.31 (95% CI 3.16-3.46) for 3 symptoms and 4.69 (95% CI 4.51-4.88) for 4 or more symptoms. Among participants with nonempty sequences, the most common sequence beginning with an out-of-facility action was offline medication purchase followed by no subsequent reported action (6058/26,494, 22.87%). Digital health engagement was lowest among adults aged 60 years or older. Conclusions: Most reported ARI episodes did not involve in-person facility attendance and may be underrepresented in routine facility-based surveillance. Digital health behaviors identified potential complementary signals for some episodes, while common pathways involving offline medication purchase suggest that pharmacy-derived data may provide additional information. These data sources require direct validation, and lower digital health engagement among older adults indicates that digital signals may not represent all population groups equally.

Mpox resurged globally in 2022 after five decades of African confinement. Pooling 70 studies (1970–2025) and WHO surveillance, we show hospitalisation and case-fatality fell from 33% and 3.3% pre-2022 to 10% and 0.7% during the clade-IIb pandemic. Clade-Ia remained high deadlier (≈80% admission, 9% death). Since 2024, Central Africa has again driven cases and deaths. High-income regions recorded milder, larger outbreaks; Africa continues to bear excess mortality. Targeted clade-Ia surveillance, vaccination and health-system support in Central Africa are urgently needed to curb mpox’s persistent global burden.

Background Understanding how diseases accumulate over time is crucial for managing their combined impact. We aim to identify these common pathways of multimorbidity and determine how they increase healthcare use and costs beyond the sum of single diseases. Methods We analyzed hospital records from over 600,000 patients in China between 2013 and 2021. We identified significant sequences of three diseases diagnosed over time and measured their synergistic effect by comparing the total healthcare use along a sequence to the added use of each disease occurring in isolation. Outcomes included hospital visits, length of stay, total costs, and out-of-pocket spending. We then grouped these sequences to identify common, high-impact connections between diseases, referred to as hub chains. Results Here we show that distinct disease sequences are common, with 83 pathways identified in women and 174 in men. The combined cost of a disease sequence often exceeds the sum of its parts, in 69.9% (58/83) of female and 81.0% (141/174) of male trajectories, demonstrating a synergistic effect. Pathways involving cancer-related care show the highest resource use for both sexes. We find that a small number of critical hub chains connect many sequences; analyses indicate that interrupting these hubs could reduce associated healthcare use and costs by approximately half. Conclusions This study demonstrates that specific sequences of diseases, particularly those linked by hub chains, drive disproportionate healthcare burdens. Focusing clinical interventions and policy on these high-impact pathways offers a promising strategy to alleviate system strain and improve care for patients with multimorbidity.

BACKGROUND Digital technologies increasingly shape responses to acute respiratory infection (ARI) symptoms through information seeking, consultation, medication purchase, monitoring, and access to diagnostic products or services. However, how digital health engagement overlaps with in-person facility attendance and whether digital and other out-of-facility behaviors provide complementary signals for episodes that are less visible in routine facility-based surveillance remain unclear. OBJECTIVE This study estimates the distribution of ARI episodes by in-person facility attendance and digital health engagement, describes digital and nondigital out-of-facility actions and the reported ordering of these actions, and examines subgroup differences. METHODS We conducted a population-based cross-sectional survey in 11 Chinese cities using multistage stratified random sampling. Participants reported ARI symptoms within the preceding 14 days and subsequent health-related actions. The primary digital composite included online health information seeking, AI-assisted consultation, telemedicine, online medication purchase, wearable device–based self-monitoring, digitally accessed self-administered rapid antigen testing, and at-home pathogen specimen collection. Participants were cross-classified by in-person facility attendance and digital health engagement. Weighted descriptive proportions were estimated using poststratification weights, with 95% CIs calculated using Wilson score intervals based on the Kish effective sample size. Behavioral sequences were descriptively reconstructed from retrospectively reported timing of actions using 1 representative action per reported day, with adjacent-transition CIs estimated by participant-level bootstrap resampling. Modified Poisson regression with individual-level robust variance estimation was used to estimate adjusted associations with in-person facility attendance, expressed as adjusted prevalence ratios (aPRs). RESULTS Among 247,530 participants, 68,650 reported ARI symptoms. Among symptomatic participants, 19.18% (95% CI 18.87%-19.48%) reported in-person facility attendance, and 18.94% (95% CI 18.64%-19.24%) reported at least one digital health behavior. Digital health engagement without in-person facility attendance comprised 11.20% (95% CI 10.95%-11.44%) of ARI episodes, while 7.74% (95% CI 7.54%-7.95%) involved both dimensions. Digital health engagement was positively associated with in-person facility attendance during the same episode (aPR 2.12, 95% CI 2.05-2.20). Compared with participants reporting 2 or fewer symptoms, the aPRs were 3.31 (95% CI 3.16-3.46) for 3 symptoms and 4.69 (95% CI 4.51-4.88) for 4 or more symptoms. Among participants with nonempty sequences, the most common sequence beginning with an out-of-facility action was offline medication purchase followed by no subsequent reported action (6058/26,494, 22.87%). Digital health engagement was lowest among adults aged 60 years or older. CONCLUSIONS Most reported ARI episodes did not involve in-person facility attendance and may be underrepresented in routine facility-based surveillance. Digital health behaviors identified potential complementary signals for some episodes, while common pathways involving offline medication purchase suggest that pharmacy-derived data may provide additional information. These data sources require direct validation, and lower digital health engagement among older adults indicates that digital signals may not represent all population groups equally.

Despite continuous viral evolution, it remains unclear whether SARS-CoV-2 has transitioned to transmission dynamics resembling those of other endemic respiratory pathogens in the post-pandemic era. During 2023–2025, we compared post-pandemic SARS-CoV-2 transmissibility with influenza virus (IFV) and common human coronaviruses (HCoV) transmissibility and SARS-CoV-2 transmissibility during and after the pandemic. Among 7,399 participants in 1,764 households, there were 704 acute-respiratory-infection index cases and 2,684 household contacts. Healthcare-seeking was higher for SARS-CoV-2 (17.6%) and IFV (28.1%) than HCoVs (9.8%). Post-pandemic SARS-CoV-2 household secondary attack risk (HSAR) (7.9%) was comparable to IFV (7.0%) and higher than HCoV (4.4%;P<0.05). Older adults had highest SARS-CoV-2 and HCoV transmissibility; children had highest IFV transmissibility, correlated with peak viral loads. Post-pandemic SARS-CoV-2 HSAR was lower than pandemic-period Omicron HSAR (adjusted odds ratio:3.30;95%CI:1.82–5.98) and Delta-period HSAR (aOR:2.46;95%CI:1.27–4.79). Pre-symptomatic transmission was observed for all three pathogens, highest for SARS-CoV-2 (35.7%). Our findings indicate that SARS-CoV-2 maintains high household transmissibility and requires substantial medical resources in the post-pandemic era, and non-pharmaceutical interventions and vaccination strategies that account for age-specific transmissibility and susceptibility merit study and consideration.

Background: Patients with chronic respiratory disease (CRD) face an increased risk of severe influenza complications. However, limited studies offer estimates of vaccine effectiveness (VE) against influenza within these CRD populations in China. Methods: A multicenter, retrospective, test-negative, case-control study was conducted to estimate the VE in 37 medical institutions in Shanghai, China, during the 2023/2024 and 2024/2025 seasons. We included patients with CRD who presented with acute respiratory infections and received nucleic acid amplification tests and/or rapid antigen tests. Patients with CRD with a positive test were assigned to the case group, and those with a negative test were assigned to the control group. Multivariable unconditional logistic regression was used to control potential confounders and to determine 95% confidence intervals (CIs). Results: A total of 10 711 participants, including 1650 influenza cases (5.8% vaccinated) and 9061 influenza-negative controls (7.9% vaccinated), were eligible for analysis. The combined VE over the 2 seasons was estimated to be 44.23% (95% CI: 30.45-55.75) for the study population. The VE was 42.91% (95% CI: 27.13–55.78) in the 2023/2024 season and 51.51% (95% CI: 17.70–73.61) in the 2024/2025 season. The combined VE for influenza subtypes A and B were 38.49% (95% CI: 21.75–52.27) and 62.64% (95% CI: 39.91–78.28), respectively. Conclusions: Influenza vaccination provides consistent and moderate protection to patients with CRD against medically attended influenza, regardless of the dominant circulating subtypes. Nevertheless, vaccination coverage remains suboptimal, underscoring the need to improve annual influenza vaccination uptake among patients with CRD , even amid ongoing viral antigenic evolution through shifts and drifts.

Prolonged sitting is an independent risk for mortality among cancer survivors, but whether higher dietary quality (DQ) may attenuate the detrimental effects of prolonged sitting is unknown. Therefore, this study aimed to examine the associations of prolonged sitting and DQ with mortality among cancer survivors. This study analyzed 2734 adult cancer survivors from the National Health and Nutrition Examination Survey from 2007 to 2018. Survey-weighted Cox proportional hazard models were used to evaluate the independent and combined associations of sitting time and DQ with mortality among cancer survivors. Prolonged sitting time was associated with higher all-cause and noncancer mortality risks, whereas qualified dietary quality (HEI-2015 ≥ 60) was associated with lower risks of all-cause, cancer, and noncancer mortality. In joint analyses, compared with individuals who had qualified DQ and sitting time less than 8 h/ d, those with unqualified DQ and sitting ≥ 8 h/d had significantly higher mortality risks. The corresponding hazard ratios (HRs) were 2.141 (95% CI: 1.536–2.985) for all-cause mortality, 2.534 (95% CI: 1.442–4.454) for cancer mortality, and 2.028 (95% CI: 1.368–3.008) for noncancer mortality. In contrast, among survivors with qualified DQ, prolonged daily sitting (≥ 8 h/d) was not significantly associated with increased mortality. The HRs were 1.507 (95% CI: 0.939–2.417) for all-cause mortality, 2.051 (95% CI: 0.893–4.709) for cancer mortality, and 1.293 (95% CI: 0.732–2.284) for noncancer mortality. Qualified dietary quality (HEI ≥ 60) might attenuate the increased risk of mortality associated with prolonged sitting time among cancer survivors.