The influence of the COVID-19 pandemic on identifying HIV/AIDS cases in China: an interrupted time series study.

Background: The COVID-19 pandemic has caused significant global public health challenges, and impacted HIV testing and reporting worldwide. We aimed to estimate the impact of COVID-19 polices on identifying HIV/AIDS cases in China from 2020 to 2022. Methods: We used an interrupted time series (ITS) design and seasonal autoregressive integrated moving average intervention (SARIMA Intervention) model. Monthly reported data on HIV/AIDS cases were extracted from the National Bureau of Disease Control and Prevention of China from January 2004 to August 2022. Data on Stringency Index (SI) and Economic Support Index (ESI) from January 22, 2020 to August 31, 2022 were extracted from the Oxford COVID-19 Government Response Tracker (OxCGRT). Using these, a SARIMA-Intervention model was constructed to evaluate the association between COVID-19 polices and monthly reported HIV/AIDS case numbers from January 2004 to August 2022 using auto.arima () function from R. The absolute percentage errors (APEs) compared the expected numbers generated by the SARIMA-Intervention model with actual numbers of HIV/AIDS, and was the primary outcome of this study. A second counterfactual model estimated HIV/AIDS case numbers if COVID-19 hadn't occurred in December 2019, and the mean difference between actual and predicted numbers were calculated. All statistical analyses were performed in R software (version 4.2.1) and EmpowerStats 2.0 and a P < 0.05 was considered statistically significant. Findings: The SARIMA-Intervention model indicated HIV/AIDS monthly reported cases were inversely and significantly correlated with stricter lockdown and COVID-19 related polices (Coefficient for SI = -231.24, 95% CI: -383.17, -79.32) but not with economic support polices (Coefficient for ESI = 124.27, 95% CI: -309.84, 558.38). APEs of the SARIMA-Intervention model for prediction of HIV/AIDS cases from January 2022 through August 2022, were -2.99, 5.08, -13.64, -34.04, -2.76, -1.52, -1.37 and -2.47 respectively, indicating good accuracy and underreporting of cases during COVID-19. The counterfactual model estimates between January 2020 and August 2022 an additional 1314 HIV/AIDS cases should have been established monthly if COVID-19 hadn't occurred. Interpretation: The COVID-19 pandemic influenced the allocation and acquisition of medical resources which impacted accurate monthly reporting of HIV in China. Interventions that promote continuous HIV testing and ensure the adequate provision of HIV services including remote delivery of HIV testing services (HIV self-testing) and online sexual counseling services are necessary during pandemics in future. Funding: Ministry of Science and Technology of the People's Republic of China (The grant number: 2020YFC0846300) and Fogarty International Center, National Institutes of Health, USA (The grant number: G11TW010941).

Risk Factors for Death Among the First 80 543 Coronavirus Disease 2019 (COVID-19) Cases in China: Relationships Between Age, Underlying Disease, Case Severity, and Region.

BACKGROUND: Knowledge of COVID-19 epidemiology remains incomplete and crucial questions persist. We aimed to examine risk factors for COVID-19 death. METHODS: A total of 80 543 COVID-19 cases reported in China, nationwide, through 8 April 2020 were included. Risk factors for death were investigated by Cox proportional hazards regression and stratified analyses. RESULTS: Overall national case-fatality ratio (CFR) was 5.64%. Risk factors for death were older age (≥80: adjusted hazard ratio, 12.58; 95% confidence interval, 6.78-23.33), presence of underlying disease (1.33; 1.19-1.49), worse case severity (severe: 3.86; 3.15-4.73; critical: 11.34; 9.22-13.95), and near-epicenter region (Hubei: 2.64; 2.11-3.30; Wuhan: 6.35; 5.04-8.00). CFR increased from 0.35% (30-39 years) to 18.21% (≥70 years) without underlying disease. Regardless of age, CFR increased from 2.50% for no underlying disease to 7.72% for 1, 13.99% for 2, and 21.99% for ≥3 underlying diseases. CFR increased with worse case severity from 2.80% (mild) to 12.51% (severe) and 48.60% (critical), regardless of region. Compared with other regions, CFR was much higher in Wuhan regardless of case severity (mild: 3.83% vs 0.14% in Hubei and 0.03% elsewhere; moderate: 4.60% vs 0.21% and 0.06%; severe: 15.92% vs 5.84% and 1.86%; and critical: 58.57% vs 49.80% and 18.39%). CONCLUSIONS: Older patients regardless of underlying disease and patients with underlying disease regardless of age were at elevated risk of death. Higher death rates near the outbreak epicenter and during the surge of cases reflect the deleterious effects of allowing health systems to become overwhelmed.

Guidance for Health Care Leaders During the Recovery Stage of the COVID-19 Pandemic: A Consensus Statement.

Importance: The COVID-19 pandemic is the greatest global test of health leadership of our generation. There is an urgent need to provide guidance for leaders at all levels during the unprecedented preresolution recovery stage. Objective: To create an evidence- and expertise-informed framework of leadership imperatives to serve as a resource to guide health and public health leaders during the postemergency stage of the pandemic. Evidence Review: A literature search in PubMed, MEDLINE, and Embase revealed 10 910 articles published between 2000 and 2021 that included the terms leadership and variations of emergency, crisis, disaster, pandemic, COVID-19, or public health. Using the Standards for Quality Improvement Reporting Excellence reporting guideline for consensus statement development, this assessment adopted a 6-round modified Delphi approach involving 32 expert coauthors from 17 countries who participated in creating and validating a framework outlining essential leadership imperatives. Findings: The 10 imperatives in the framework are: (1) acknowledge staff and celebrate successes; (2) provide support for staff well-being; (3) develop a clear understanding of the current local and global context, along with informed projections; (4) prepare for future emergencies (personnel, resources, protocols, contingency plans, coalitions, and training); (5) reassess priorities explicitly and regularly and provide purpose, meaning, and direction; (6) maximize team, organizational, and system performance and discuss enhancements; (7) manage the backlog of paused services and consider improvements while avoiding burnout and moral distress; (8) sustain learning, innovations, and collaborations, and imagine future possibilities; (9) provide regular communication and engender trust; and (10) in consultation with public health and fellow leaders, provide safety information and recommendations to government, other organizations, staff, and the community to improve equitable and integrated care and emergency preparedness systemwide. Conclusions and Relevance: Leaders who most effectively implement these imperatives are ideally positioned to address urgent needs and inequalities in health systems and to cocreate with their organizations a future that best serves stakeholders and communities.

Coronavirus disease 2019 outbreak in Beijing's Xinfadi Market, China: a modeling study to inform future resurgence response.

BACKGROUND: A local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing's XFD market and inform future response efforts of resurgence across regions. METHODS: A modified susceptible-exposed-infectious-recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI). RESULTS: Our results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31-77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment. CONCLUSIONS: This study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere.

Risk factors and on-site simulation of environmental transmission of SARS-CoV-2 in the largest wholesale market of Beijing, China.

From June 11, 2020, a surge in new cases of coronavirus disease 2019 (COVID-19) in the largest wholesale market of Beijing, the Xinfadi Market, leading to a second wave of COVID-19 in Beijing, China. Understanding the transmission modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the personal behaviors and environmental factors contributing to viral transmission is of utmost important to curb COVID-19 rise. However, currently these are largely unknown in food markets. To this end, we completed field investigations and on-site simulations in areas with relatively high infection rates of COVID-19 at Xinfadi Market. We found that if goods were tainted or personnel in market was infected, normal transaction behaviors between sellers and customers, daily physiological activities, and marketing activities could lead to viral contamination and spread to the surroundings via fomite, droplet or aerosol routes. Environmental factors such as low temperature and high humidity, poor ventilation, and insufficient hygiene facilities and disinfection practices may contribute to viral transmission in Xinfadi Market. In addition, precautionary control strategies were also proposed to effectively reduce the clustering cases of COVID-19 in large-scale wholesale markets.

One Hundred Days of Coronavirus Disease 2019 Prevention and Control in China.

The epidemic of novel coronavirus disease was first reported in China in late December 2019 and was brought under control after some 2 months in China. However, it has become a global pandemic, and the number of cases and deaths continues to increase outside of China. We describe the emergence of the pandemic, detail the first 100 days of China's response as a phase 1 containment strategy followed by phase 2 containment, and briefly highlight areas of focus for the future. Specific, simple, and pragmatic strategies used in China for risk assessment, prioritization, and deployment of resources are described. Details of implementation, at different risk levels, of the traditional public health interventions are shared. Involvement of society in mounting a whole country response and challenges experienced with logistics and supply chains are described. Finally, the methods China is employing to cautiously restart social life and economic activity are outlined.

COVID-19 seeding time and doubling time model: an early epidemic risk assessment tool.

BACKGROUND: As COVID-19 makes its way around the globe, each nation must decide when and how to respond. Yet many knowledge gaps persist, and many countries lack the capacity to develop complex models to assess risk and response. This paper aimed to meet this need by developing a model that uses case reporting data as input and provides a four-tiered risk assessment output. METHODS: We used publicly available, country/territory level case reporting data to determine median seeding number, mean seeding time (ST), and several measures of mean doubling time (DT) for COVID-19. We then structured our model as a coordinate plane with ST on the x-axis, DT on the y-axis, and mean ST and mean DT dividing the plane into four quadrants, each assigned a risk level. Sensitivity analysis was performed and countries/territories early in their outbreaks were assessed for risk. RESULTS: Our main finding was that among 45 countries/territories evaluated, 87% were at high risk for their outbreaks entering a rapid growth phase epidemic. We furthermore found that the model was sensitive to changes in DT, and that these changes were consistent with what is officially known of cases reported and control strategies implemented in those countries. CONCLUSIONS: Our main finding is that the ST/DT Model can be used to produce meaningful assessments of the risk of escalation in country/territory-level COVID-19 epidemics using only case reporting data. Our model can help support timely, decisive action at the national level as leaders and other decision makers face of the serious public health threat that is COVID-19.