Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data.

BACKGROUND: Twitter has become a dominant source of public health data and a widely used method to investigate and understand public health-related issues internationally. By leveraging big data methodologies to mine Twitter for health-related data at the individual and community levels, scientists can use the data as a rapid and less expensive source for both epidemiological surveillance and studies on human behavior. However, limited reviews have focused on novel applications of language analyses that examine human health and behavior and the surveillance of several emerging diseases, chronic conditions, and risky behaviors. OBJECTIVE: The primary focus of this scoping review was to provide a comprehensive overview of relevant studies that have used Twitter as a data source in public health research to analyze users' tweets to identify and understand physical and mental health conditions and remotely monitor the leading causes of mortality related to emerging disease epidemics, chronic diseases, and risk behaviors. METHODS: A literature search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extended guidelines for scoping reviews was used to search specific keywords on Twitter and public health on 5 databases: Web of Science, PubMed, CINAHL, PsycINFO, and Google Scholar. We reviewed the literature comprising peer-reviewed empirical research articles that included original research published in English-language journals between 2008 and 2021. Key information on Twitter data being leveraged for analyzing user language to study physical and mental health and public health surveillance was extracted. RESULTS: A total of 38 articles that focused primarily on Twitter as a data source met the inclusion criteria for review. In total, two themes emerged from the literature: (1) language analysis to identify health threats and physical and mental health understandings about people and societies and (2) public health surveillance related to leading causes of mortality, primarily representing 3 categories (ie, respiratory infections, cardiovascular disease, and COVID-19). The findings suggest that Twitter language data can be mined to detect mental health conditions, disease surveillance, and death rates; identify heart-related content; show how health-related information is shared and discussed; and provide access to users' opinions and feelings. CONCLUSIONS: Twitter analysis shows promise in the field of public health communication and surveillance. It may be essential to use Twitter to supplement more conventional public health surveillance approaches. Twitter can potentially fortify researchers' ability to collect data in a timely way and improve the early identification of potential health threats. Twitter can also help identify subtle signals in language for understanding physical and mental health conditions.

Insights from Government Officials on Strategies and Practices for Managing the Covid-19 Pandemic: A Qualitative Study

Background: The study focuses on the challenges faced by government officials in implementing public health interventions to control the spread of COVID-19 in the Lahore District, Pakistan. Material(s) and Method(s): This qualitative study used in-depth interviews to collect data from 45 government officials involved in implementing COVID-19 control measures in Lahore District. Result(s): The study identified several themes related to the challenges faced by government officials, including contact tracing and coordination, disease management and vaccination, public perception and engagement, international travellers management, and implementation strategies. Strategies implemented to address the challenges posed by the pandemic included the utilization of technology, provision of training to staff, coordination with other organizations, identification of high transmission areas, and targeting specific communities or populations at higher risk of infection. Conclusion(s): The effective management of the COVID-19 pandemic requires a coordinated and multi-faceted response that incorporates various strategies and practices aimed at controlling the spread of the disease and mitigating its impact on communities. The authors recommend prioritizing clear and consistent communication, community engagement, and capacity building in pandemic management strategies.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Assessing the impacts of COVID-19 vaccination programme's timing and speed on health benefits, cost-effectiveness, and relative affordability in 27 African countries.

BACKGROUND: The COVID-19 vaccine supply shortage in 2021 constrained roll-out efforts in Africa while populations experienced waves of epidemics. As supply improves, a key question is whether vaccination remains an impactful and cost-effective strategy given changes in the timing of implementation. METHODS: We assessed the impact of vaccination programme timing using an epidemiological and economic model. We fitted an age-specific dynamic transmission model to reported COVID-19 deaths in 27 African countries to approximate existing immunity resulting from infection before substantial vaccine roll-out. We then projected health outcomes (from symptomatic cases to overall disability-adjusted life years (DALYs) averted) for different programme start dates (01 January to 01 December 2021, n = 12) and roll-out rates (slow, medium, fast; 275, 826, and 2066 doses/million population-day, respectively) for viral vector and mRNA vaccines by the end of 2022. Roll-out rates used were derived from observed uptake trajectories in this region. Vaccination programmes were assumed to prioritise those above 60 years before other adults. We collected data on vaccine delivery costs, calculated incremental cost-effectiveness ratios (ICERs) compared to no vaccine use, and compared these ICERs to GDP per capita. We additionally calculated a relative affordability measure of vaccination programmes to assess potential nonmarginal budget impacts. RESULTS: Vaccination programmes with early start dates yielded the most health benefits and lowest ICERs compared to those with late starts. While producing the most health benefits, fast vaccine roll-out did not always result in the lowest ICERs. The highest marginal effectiveness within vaccination programmes was found among older adults. High country income groups, high proportions of populations over 60 years or non-susceptible at the start of vaccination programmes are associated with low ICERs relative to GDP per capita. Most vaccination programmes with small ICERs relative to GDP per capita were also relatively affordable. CONCLUSION: Although ICERs increased significantly as vaccination programmes were delayed, programmes starting late in 2021 may still generate low ICERs and manageable affordability measures. Looking forward, lower vaccine purchasing costs and vaccines with improved efficacies can help increase the economic value of COVID-19 vaccination programmes.

SARS-CoV-2 incidence and risk factors in a national, community-based prospective cohort of U.S. adults.

BACKGROUND: Prospective cohort studies of SARS-CoV-2 incidence complement case-based surveillance and cross-sectional seroprevalence surveys. METHODS: We estimated the incidence of SARS-CoV-2 infection in a national cohort of 6,738 U.S. adults, enrolled March-August 2020. Using Poisson models, we examined the association of social distancing and a composite epidemiologic risk score with seroconversion. The risk score was created using LASSO regression to identify factors predictive of seroconversion. The selected factors were household crowding, confirmed case in household, indoor dining, gathering with groups ≥ 10, and no masking in gyms/salons. RESULTS: Among 4,510 individuals with ≥1 serologic test, 323 (7.3%, 95% confidence interval [CI] 6.5%-8.1%) seroconverted by January 2021. Among 3,422 participants seronegative in May-September 2020 and retested during November 2020-January 2021, 161 seroconverted over 1,646 person-years of follow-up (9.8 per 100 person-years [95%CI 8.3-11.5]). Seroincidence rate was lower among females compared to males (IRR: 0.69, 95% CI 0.50-0.94) and higher among Hispanic (IRR: 2.09, 95% CI 1.41-3.05) participants compared to White non-Hispanic. In adjusted models, participants who reported social distancing with people they did not know (IRRalways vs. never: 0.42, 95% CI 0.20-1.0) and with people they knew (IRRalways vs. never 0.64, 95%CI 0.39-1.06; IRRsometimes vs. never 0.60, 95% CI 0.38-0.96) had lower seroconversion risk. Seroconversion risk increased with epidemiologic risk score (IRRmedium vs. low 1.68, 95% CI 1.03-2.81; IRRhigh vs. low 3.49, 95% CI 2.26-5.58). Only 29% of those who seroconverted reported isolating and 19% were asked about contacts. CONCLUSION: Modifiable risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the U.S.

Non-pharmacological interventions of travel restrictions and cancelation of public events had a major reductive mortality affect during pre-vaccination coronavirus disease 2019 period.

Background: The coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods. Methods: The COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model. Results: During the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06). Conclusion: Continued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality; however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, "cancelation of public events and gatherings" become more important for COVID-19 mortality.

Experiences of face mask use during the COVID-19 pandemic: A qualitative study.

The use of face masks and coverings has been a central component of efforts to mitigate the impact of the COVID-19 pandemic and has been legally mandated in some countries. Most academic studies to date, however, have focussed primarily on its effectiveness in reducing SARS-CoV-2 transmission, largely neglecting the social dimensions of mask mandates. In this narrative interview-based study, we consider experiences of face masks, with a particular focus on groups considered to be at a potential disadvantage from compulsory masking. Drawing on 40 telephone, video-call and e-mail interviews, we highlight the impact of inconsistent communication and the notion of mask wearing as an act of altruism on participants' experiences. In particular, we show how intolerance towards individuals who did not wear masks could result in stigma and exclusion, regardless of the legitimacy of their reasons. We suggest that more is needed to mitigate the 'dark side' of discourses of collective effort and altruism at a time of societal stress and fracture, and to account for the needs and interests of groups for whom compulsory masking may result in further marginalisation.

Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study.

BACKGROUND: COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic. OBJECTIVE: Nonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China. METHODS: Time series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People's Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak. RESULTS: We found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude. CONCLUSIONS: Our results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases.

The impact of community closures among nonessential and essential workers, Nashville, Tennessee: A cross-sectional study.

Background and Aims: The effects of community closures and relaxing social distancing restrictions on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) by occupational risk remain unclear. Therefore, we evaluated the impact of community closures and reopening phases with the prevalence of testing SARS-CoV-2-positive among nonessential and essential workers. Methods: We constructed a cross-sectional cohort from March 20 to July 31, 2020, of 344 adults from Metropolitan Nashville, Tennessee. We performed an unconditional logistic regression model to evaluate the impact of community closures and phase implementation on testing SARS-CoV-2 positive by occupation to estimate adjusted prevalence odds ratios (aPORs) and 95% confidence intervals (CIs). Results: During a stay-at-home/Phase I order, those with non-essential occupations had 59% decreased prevalence odds (aPOR:0.41; 95% CI: 0.20-0.84) of testing SARS-CoV-2-positive compared to when no restrictions were in place. Persons with essential occupations had four times the prevalence odds of testing SARS-CoV-2-positive (aPOR:4.19; 95% CI:1.57-11.18) compared with nonessential occupations when no community restrictions were established. Conclusion: Stay-at-home restrictions were associated with a lower risk of SARS-CoV-2 infection in the community for nonessential workers. Essential employees remained at increased risk for SARS-CoV-2, including when no community restrictions were in place and vaccines were not available. This study supports targeting prevention measures for these high-risk occupations.

Optimal timing and effectiveness of COVID-19 outbreak responses in China: a modelling study.

BACKGROUND: In January 2020, an outbreak of atypical pneumonia caused by a novel coronavirus, SARS-CoV-2, was reported in Wuhan, China. On Jan 23, 2020, the Chinese government instituted mitigation strategies to control spread. Most modeling studies have focused on projecting epidemiological outcomes throughout the pandemic. However, the impact and optimal timing of different mitigation approaches have not been well-studied. METHODS: We developed a mathematical model reflecting SARS-CoV-2 transmission dynamics in an age-stratified population. The model simulates health and economic outcomes from Dec 1, 2019 through Mar 31, 2020 for cities including Wuhan, Chongqing, Beijing, and Shanghai in China. We considered differences in timing and duration of three mitigation strategies in the early phase of the epidemic: city-wide quarantine on Wuhan, travel history screening and isolation of travelers from Wuhan to other Chinese cities, and general social distancing. RESULTS: Our model estimated that implementing all three mitigation strategies one week earlier would have averted 35% of deaths in Wuhan (50% in other cities) with a 7% increase in economic impacts (16-18% in other cities). One week's delay in mitigation strategy initiation was estimated to decrease economic cost by the same amount, but with 35% more deaths in Wuhan and more than 80% more deaths in the other cities. Of the three mitigation approaches, infections and deaths increased most rapidly if initiation of social distancing was delayed. Furthermore, social distancing of working-age adults was most critical to reducing COVID-19 outcomes versus social distancing among children and/or the elderly. CONCLUSIONS: Optimizing the timing of epidemic mitigation strategies is paramount and involves weighing trade-offs between preventing infections and deaths and incurring immense economic impacts. City-wide quarantine was not as effective as city-wide social distancing due to its much higher daily cost than social distancing. Under typical economic evaluation standards, the optimal timing for the full set of control measures would have been much later than Jan 23, 2020 (status quo).

The impacts of COVID-19 on clean energy labor markets: Evidence from multifaceted analysis of public health interventions and COVID-health factors.

COVID-19 pandemic has affected clean energy labor market. Using real-time job vacancy data, this study analyzes the impacts of the pandemic on the U.S. clean energy labor market in 2020, including biomass, energy efficiency (EE), electric vehicle (EV), power/microgrid, solar, and wind industries. This study identifies how COVID-health factors and public health interventions influence clean energy job availability during the early COVID pandemic. Overall, California had the most energy jobs and experienced a significant decrease in April 2020. EV and solar had the highest percentages of job vacancies during the pandemic in general. Still, lockdowns had the most severe influence on EE and wind jobs. Stay-at-home orders negatively affected clean energy job vacancies in biomass, EV, power/microgrid, and wind. Social-gathering restrictions, however, did not have much influence. Increased COVID tests at the state level had the strongest and most positive influence on clean energy job postings, indicating the importance of a state's ability to manage public health infrastructure or crisis issues. COVID hospitalizations negatively influenced the job vacancies in biomass and wind but did not affect the other four sectors; conversely, as COVID death numbers increased, the number of jobs in biomass, EV, power grid, solar, and wind decreased, but not in EE jobs.

Exploring the Impact of Government Interventions on COVID-19 Pandemic Spread in Kuwait

To model the trajectory of the pandemic in Kuwait from February 24, 2020 to February 28, 2021, the authors used two modeling procedures-auto regressive integrated moving average (ARIMA) with structural breaks and multivariate adaptive regression splines (MARS)-and then mapped the key breakpoints of the models to the set of government-enforced interventions. The MARS model, as opposed to the ARIMA model, provides a more precise interpretation of the intervention's effects. It demonstrates that partial and total lockdown interventions were highly effective in reducing the number of confirmed cases. When some interventions, such as enforcing regional curfews, closing workplaces, and imposing travel restrictions, were combined, their impact became significant. MARS method is recommended when exploring the impact of interventions on the spread of a disease. It does not require any prior assumptions about the statistical distribution of data, does not affect data collinearity, has simple and transparent functions, and allows for a more accurate analysis of intervention results.

Critical timing and extent of public health interventions to control outbreaks dominated by SARS-CoV-2 variants in Australia: a mathematical modelling study.

OBJECTIVES: The exact characteristics of a coronavirus disease 2019 (COVID-19) outbreak that trigger public health interventions are poorly defined. The aim of this study was to assess the critical timing and extent of public health interventions to contain COVID-19 outbreaks in Australia. METHODS: A practical model was developed using existing epidemic data in Australia. The effective combinations of public health interventions and the critical number of daily cases for intervention commencement under various scenarios of changes in transmissibility of new variants and vaccination coverage were quantified. RESULTS: In the past COVID-19 outbreaks in four Australian states, the number of reported cases on the day that interventions commenced strongly predicted the size and duration of the outbreaks. In the early phase of an outbreak, containing a wildtype-dominant epidemic to a low level (≤10 cases/day) would require effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches six. Containing an Alpha-dominant epidemic would require more stringent interventions that commence earlier. For the Delta variant, public health interventions alone would not contain the epidemic unless the vaccination coverage was ≥70%. CONCLUSIONS: This study highlights the importance of early and decisive action in the initial phase of an outbreak. Vaccination is essential for containing variants.

Commentary on “Adapted guided self-help booklets for supporting the wellbeing of people with intellectual disabilities during the COVID-19 pandemic”

Purpose: The purpose of this paper is to provide a commentary on “Adapted guided self-help booklets for supporting the wellbeing of people with intellectual disabilities during the COVID-19 pandemic” (Jahoda et al.). Design/methodology/approach: This paper considers health and wellbeing for people with intellectual disabilities in the context of public health interventions and public health research. Findings: Consideration is given to the evidence base for self-management, self-help and behavioural change interventions and the need to consider systemic support for promoting the health and wellbeing of people with intellectual disabilities. Originality/value: Guided self-help and self-management techniques have a role in the health promotion of people with intellectual disabilities. Reciprocal sharing between public health researchers and intellectual disability researchers is needed to further the research, policy and service agenda to better promote health and wellbeing for this underserved group. © 2021, Emerald Publishing Limited.

Statistical indicators of compliance with anti-COVID-19 public health measures at European airports.

International travel and the infrastructures involved are key elements in controlling and predicting the number of infections by an infectious disease (specifically COVID-19 cases). This research presents the rates or percentages of compliance with COVID-19 mitigation measures at several international airports in Europe (Madrid, Dublin, Paris-Charles de Gaulle, Zurich, Barcelona, and Bilbao). A structured survey called the COVID-19 Measures Implementation Rate at Airports (MIRA) was developed. First, the validity and reliability of the measurements obtained by MIRA were analyzed. A total of 1239 volunteers (passengers, cabin crew, and ground crew) participated in the study and answered the MIRA questionnaire. Second, once the validity and reliability of the measurements were assured, the rates or percentages of cases that observed compliance with the mitigation measures were calculated. The results indicated that participants perceived a low degree of compliance with sanitary measures in their international travel (the proportions ranged from 52.6% to 59%). The airports with the highest compliance with mitigation measures were the Dublin (with a rate of 70%) and Zurich airports (with a rate of 69.1%). In conclusion, the percentages could be low due to the ineffective implementation of some of the mitigation measures. The low percentages are not related to the health measures themselves. The implications of mitigation measures for containing the transmission of infectious diseases such as COVID-19 are discussed.

Changes in Incidence of Notifiable Infectious Diseases in China Under the Prevention and Control Measures of COVID-19.

Aim: The aim of this study was to analyze the changes in incidence of notifiable infectious diseases in China under the prevention and control measures of COVID-19. Methods: Using descriptive epidemiological methods, data were collected from the official website of the Health Commission of the People's Republic of China, and the prevalence characteristics of notifiable infectious diseases in the country in 2020 were analyzed and compared with the historical data in 2019. Monthly reporting data on influenza and tuberculosis from 2015 to 2019 were also collected. Results: Except for COVID-19, the total number of notifiable infectious diseases cases in 2020 was 6,366,176, a decrease of 41.38% year-on-year compared with 2019. Category B and C notifiable infectious diseases decreased by 14.84 and 54.98% year-on-year, respectively (P < 0.01). The top three incidence rates were influenza (87.63 cases/100,000), hepatitis B (81.36 cases/100,000) and other infectious diarrhea (76.33 cases/100,000). Three types of diseases with the largest decline were influenza (-2,280,502 cases), hand-foot-mouth disease (-1,174,588 cases), and other infectious diarrhea diseases (-275,746 cases). Compared with 2019, respiratory infectious diseases were reported to be in the largest decline in 2020, followed by intestinal infectious diseases, blood-borne and sexually transmitted diseases, natural foci, and insect-borne infectious diseases. The monthly reported incidences of influenza and tuberculosis in 2020 were lower than the average of the previous 5 years. Conclusion: In 2020, the incidence of most notifiable infectious diseases in China showed a downward trend, non-pharmaceutical interventions (NPIs)such as the wearing of masks, frequent hand-washing, more ventilation, less gathering, etc, played an positive role in the prevention and control of respiratory and intestinal infectious diseases. The various public health intervention strategies and measures adopted by China to contain COVID-19 can provide a reference for the prevention and control of infectious diseases in other countries.

Evaluation of China's Hubei control strategy for COVID-19 epidemic: an observational study.

BACKGROUND: To fight against COVID-19, many policymakers are wavering on stricter public health interventions. Examining the different strategies both in and out of China's Hubei province, which contained the epidemic in late February 2020, could yield valuable guidance for the management of future pandemics. This study assessed the response process and estimated the time-varying effects of the Hubei control strategy. Analysis of these strategies provides insights for the design and implementation of future policy interventions. METHODS: We retrospectively compared the spread and control of COVID-19 between China's Hubei (excluding Wuhan) and non-Hubei areas using data that includes case reports, human mobility, and public health interventions from 1 January to 29 February 2020. Static and dynamic risk assessment models were developed to statistically investigate the effects of the Hubei control strategy on the virus case growth after adjusting importation risk and policy response timing with the non-Hubei strategy as a control. RESULTS: The analysis detected much higher but differential importation risk in Hubei. The response timing largely coincided with the importation risk in non-Hubei areas, but Hubei areas showed an opposite pattern. Rather than a specific intervention assessment, a comprehensive comparison showed that the Hubei control strategy implemented severe interventions characterized by unprecedentedly strict and 'monitored' self-quarantine at home, while the non-Hubei strategy included physical distancing measures to reduce contact among individuals within or between populations. In contrast with the non-Hubei control strategy, the Hubei strategy showed a much higher, non-linear and gradually diminishing protective effect with at least 3 times fewer cases. CONCLUSIONS: A risk-based control strategy was crucial to the design of an effective response to the COVID-19 outbreak. Our study demonstrates that the stricter Hubei strategy achieves a stronger controlling effect compared to other strategies. These findings highlight the health benefits and policy impacts of precise and differentiated strategies informed by constant monitoring of outbreak risk.

Dual-Gendered Leadership: Gender-Inclusive Scientific-Political Public Health Communication Supporting Government COVID-19 Responses in Atlantic Canada.

This research aims to identify the influence of woman leadership on improving the traditional man-dominated scientific-political communication towards positive COVID-19-driven public health interventions. Across Canada, dual-gendered leadership (women chief medical officers and men prime minister/premiers) at both federal and provincial levels illustrated a positive approach to "flatten the curve" during the first and second waves of COVID-19. With the four provinces of New Brunswick, Newfoundland and Labrador, Nova Scotia, and Prince Edward Island, Atlantic Canada formed the "Atlantic Bubble", which has become a great example domestically and internationally of successfully mitigating the pandemic while maintaining societal operation. Three provinces have benefitted from this complementary dual-gendered leadership. This case study utilized a scoping media coverage review approach, quantitatively examining how gender-inclusive scientific-political cooperation supported effective provincial responses in Atlantic Canada during the first two waves of COVID-19. This case study discovers that (1) at the provincial government level, woman leadership of mitigation, advocating, and coordination encouraged provincial authorities to adapt science-based interventions and deliver consistent and supportive public health information to the general public; and (2) at the community level, this dual-gendered leadership advanced community cohesion toward managing the community-based spread of COVID-19. Future studies may apply a longitudinal, retrospective approach with Canada-wide or cross-national comparison to further evaluate the strengths and weaknesses of dual-gendered leadership.

Public Health Interventions for COVID-19 Reduce Kawasaki Disease in Taiwan.

BACKGROUND: Kawasaki disease (KD) is a syndrome of unknown cause that results in high fever and coronary vasculitis in children. The incidence of KD increased in Taiwan over the past few decades. Taiwanese government executed domains of early screening, effective methods for isolation or quarantine, and digital technologies for identifying potential cases for the early elimination strategy for coronavirus disease 2019 (COVID-19) and public health interventions for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or COVID-19 pandemic, leading to an effective reduction of the risk of airway infections in children. The purpose of this study is to analyze whether those public health interventions reduce the incidence of KD in 2020. METHODS: Patients with KD who visited Chang Gung Memorial Hospital (CGMH) between 1 January, 2018, and 31 December, 2020 were included for trend analysis. This is a retrospective case series study conducted at the CGMH, which consists of a network of seven hospital branches equipped with more than 10,000 beds in different areas of Taiwan. RESULTS: Compared with the 2018 and 2019 databases, the incidence of KD decreased significantly by 30% and 31%, respectively (p < 0.05) in 2020, when public health interventions were comprehensively implemented in Taiwan. This result shows that the incidence of KD decreased during the COVID-19 pandemic in Taiwan without change of the presentation KD (typical or incomplete) and percentage of IVIG resistance in 2020. CONCLUSION: As public health interventions were carried out for the SARS-CoV-2 pandemic, the incidence of KD was significantly reduced in Taiwan. Is KD a preventable disease?

The immediate and subsequent effects of public health interventions for COVID-19 on the leisure and recreation industry.

Public health interventions to combat COVID-19 can be viewed as an exogenous shock to the economy, especially for industries-such as leisure, recreation, and tourism-that rely heavily on human mobility. This study investigates whether and how exactly the economic impact of government public health policies varies over time. Focusing on the leisure and recreation industry, we use data for 131 countries/regions from February to May 2020 and employ generalized difference-in-differences models to investigate the short- and longer-term effects of public health policies. We find that stricter policies lead, on average, to an immediate 9.2-percentage-point drop in leisure and recreation participation. Even so, that industry recovers in about seven weeks after a COVID-19 outbreak in countries/regions that undertake active interventions. After thirteen weeks, leisure and recreation involvement recovers to 70% of pre-pandemic levels in a place that actively intervened but stagnates at about 40% in one that did not.

Impact of Nonpharmacological Public Health Interventions on Epidemiological Parameters of COVID-19 Pandemic in India.

Background Public health interventions are epidemiologically sound and cost-effective methods to control disease burden. Non-pharmacological public health interventions are the only mode to control diseases in the absence of medication. Objective To find the impact of public health interventions on the epidemiological indicators of disease progression. Methods This is a secondary data analysis done on COVID-19 data. The median doubling time and R0 were calculated for a rolling period of seven days. Interventions were scored from zero to three with an increasing level of stringency. Multivariate linear regression was performed to find the role of individual interventions on R0 and the median doubling time. Results The highest intervention score was reported in the lockdown phase, which gradually decreased to the lowest level of 22. The R0 values settled to a level of 1.25, and the median doubling time increased to 20 days at the end of the study. Public awareness and public health laws were found to be related to both R0 and the median doubling time in the pre-lockdown phase only. Conclusion The implementation of interventions at the ground level is one of the key factors in the success of public health interventions. Post implementation, poor effectiveness of many interventions is evident from the study. Further, studies related to the sequence of interventions are required to further analyze the poor effect of the interventions.