Prevalence of respiratory pathogens and risk of developing pneumonia under non-pharmaceutical interventions in Suzhou, China.

This study aims to evaluate the impact of non-pharmaceutical interventions (NPIs) on the prevalence of respiratory pathogens among hospitalised children with acute respiratory infections (ARIs) in Suzhou. Children with ARIs admitted to the Children's Hospital of Soochow University between 1 September 2021 and 31 December 2022 and subjected to 13 respiratory pathogen multiplex PCR assays were included in the study. We retrospectively collected demographic details, results of respiratory pathogen panel tests, and discharge diagnostic information of the participants, and described the age and seasonal distribution of respiratory pathogens and risk factors for developing pneumonia. A total of 10,396 children <16 years of age, including 5,905 males and 4,491 females, were part of the study. The positive rates of the 11 respiratory pathogen assays were 23.3% (human rhinovirus (HRV)), 15.9% (human respiratory syncytial virus (HRSV)), 10.5% (human metapneumovirus (HMPV)), 10.3% (human parainfluenza virus (HPIV)), 8.6% (mycoplasma pneumoniae (MP)), 5.8% (Boca), 3.5% (influenza A (InfA)), 2.9% (influenza B (InfB)), 2.7% (human coronavirus (HCOV)), 2.0% (adenovirus (ADV)), and 0.5% (Ch), respectively. Bocavirus and HPIV detection peaked during the period from September to November (autumn), and MP and HMPV peaked in the months of November and December. The peak of InfA detection was found to be in summer (July and August), whereas the InfB peak was observed to be in winter (December, January, and February). HRSV and HRV predominated in the <3 years age group. HRV and HMPV were common in the 3-6 years group, whereas MP was predominant in the ≥6 years group. MP (odds ratio (OR): 70.068, 95%CI: 32.665-150.298, P < 0.01), HMPV (OR: 6.493, 95%CI: 4.802-8.780, P < 0.01), Boca (OR: 3.300, 95%CI: 2.186-4.980, P < 0.01), and HRSV (OR: 2.649, 95%CI: 2.089-3.358, P < 0.01) infections were more likely to develop into pneumonia than the other pathogens. With the use of NPIs, HRV was the most common pathogen in children with ARIs, and MP was more likely to progress to pneumonia than other pathogens.

Combined Infection Control Interventions Protect Essential Food Workers from Occupational Exposures to SARS-CoV-2 in the Agricultural Environment.

Essential food workers experience elevated risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection due to prolonged occupational exposures in food production and processing areas, shared transportation (car or bus), and employer-provided shared housing. Our goal was to quantify the daily cumulative risk of SARS-CoV-2 infection for healthy susceptible produce workers and to evaluate the relative reduction in risk attributable to food industry interventions and vaccination. We simulated daily SARS-CoV-2 exposures of indoor and outdoor produce workers through six linked quantitative microbial risk assessment (QMRA) model scenarios. For each scenario, the infectious viral dose emitted by a symptomatic worker was calculated across aerosol, droplet, and fomite-mediated transmission pathways. Standard industry interventions (2-m physical distancing, handwashing, surface disinfection, universal masking, ventilation) were simulated to assess relative risk reductions from baseline risk (no interventions, 1-m distance). Implementation of industry interventions reduced an indoor worker's relative infection risk by 98.0% (0.020; 95% uncertainty interval [UI], 0.005 to 0.104) from baseline risk (1.00; 95% UI, 0.995 to 1.00) and an outdoor worker's relative infection risk by 94.5% (0.027; 95% UI, 0.013 to 0.055) from baseline risk (0.487; 95% UI, 0.257 to 0.825). Integrating these interventions with two-dose mRNA vaccinations (86 to 99% efficacy), representing a worker's protective immunity to infection, reduced the relative infection risk from baseline for indoor workers by 99.9% (0.001; 95% UI, 0.0002 to 0.005) and outdoor workers by 99.6% (0.002; 95% UI, 0.0003 to 0.005). Consistent implementation of combined industry interventions, paired with vaccination, effectively mitigates the elevated risks from occupationally acquired SARS-CoV-2 infection faced by produce workers. IMPORTANCE This is the first study to estimate the daily risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection across a variety of indoor and outdoor environmental settings relevant to food workers (e.g., shared transportation [car or bus], enclosed produce processing facility and accompanying breakroom, outdoor produce harvesting field, shared housing facility) through a linked quantitative microbial risk assessment framework. Our model has demonstrated that the elevated daily SARS-CoV-2 infection risk experienced by indoor and outdoor produce workers can be reduced below 1% when vaccinations (optimal vaccine efficacy, 86 to 99%) are implemented with recommended infection control strategies (e.g., handwashing, surface disinfection, universal masking, physical distancing, and increased ventilation). Our novel findings provide scenario-specific infection risk estimates that can be utilized by food industry managers to target high-risk scenarios with effective infection mitigation strategies, which was informed through more realistic and context-driven modeling estimates of the infection risk faced by essential food workers daily. Bundled interventions, particularly if they include vaccination, yield significant reductions (>99%) in daily SARS-CoV-2 infection risk for essential food workers in enclosed and open-air environments.

The Unexpected Positive Outcomes for Summer Camps in the Time of COVID-19

The COVID-19 pandemic completely upended the camping industry, posing unique and significant challenges to youth summer engagement experiences, with many camps choosing not to operate in the summer of 2020. These canceled programs resulted in staff layoffs and loss of revenue. Some state requirements necessitated camp closures, while other camps closed due to uncertainty about the ability to provide a safe, healthy camp experience that retained the essence of summer camp. The small portion of camps that did open were forced to be cre-ative in how they offered programs. Some camps chose to run limited in-person programs, some offered family camps for family units, while others transitioned to virtual camp experiences. For these camps that did run in some capacity, several national organizations were able to gather data regarding operational challenges and benefits. Using document analysis, this project examined research findings from four national camp organizations. This cross-organizational analysis high-lights the experiences of camps offering in-person summer programs and services in implementing nonpharmaceutical interventions (NPIs) to minimize the risk of COVID-19 transmission in 2020. Camps used a variety of NPIs that involved both personal responsibility and community cooperation to create a camp experience that was socially distant and as sanitary as possible. This study also examines the experiences of camps offering virtual programs and services as a means to connect with individuals and support socialization needs of youth. These virtual programs varied widely, but all provided youth the opportunity to connect with like-minded campers and staff to have community building experiences despite isolation. In the context of many COVID-19 challenges, this study identifies positive benefits associated with operating camp in the summer of 2020. These unexpected positive impacts encompass health center operations, food service, programmatic changes, changes to the structure of camper units, and a shifting focus toward mental, emo-tional, and social health. Many of these positive outcomes are perceived by camp administrators as beneficial changes that will likely remain after the pandemic and continue to the for the foreseeable future.

Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study.

BACKGROUND: The initial wave of the COVID-19 pandemic placed a tremendous strain on health care systems worldwide. To mitigate the spread of the virus, many countries implemented stringent nonpharmaceutical interventions (NPIs), which significantly altered human behavior both before and after their enactment. Despite these efforts, a precise assessment of the impact and efficacy of these NPIs, as well as the extent of human behavioral changes, remained elusive. OBJECTIVE: In this study, we conducted a retrospective analysis of the initial wave of COVID-19 in Spain to better comprehend the influence of NPIs and their interaction with human behavior. Such investigations are vital for devising future mitigation strategies to combat COVID-19 and enhance epidemic preparedness more broadly. METHODS: We used a combination of national and regional retrospective analyses of pandemic incidence alongside large-scale mobility data to assess the impact and timing of government-implemented NPIs in combating COVID-19. Additionally, we compared these findings with a model-based inference of hospitalizations and fatalities. This model-based approach enabled us to construct counterfactual scenarios that gauged the consequences of delayed initiation of epidemic response measures. RESULTS: Our analysis demonstrated that the pre-national lockdown epidemic response, encompassing regional measures and heightened individual awareness, significantly contributed to reducing the disease burden in Spain. The mobility data indicated that people adjusted their behavior in response to the regional epidemiological situation before the nationwide lockdown was implemented. Counterfactual scenarios suggested that without this early epidemic response, there would have been an estimated 45,400 (95% CI 37,400-58,000) fatalities and 182,600 (95% CI 150,400-233,800) hospitalizations compared to the reported figures of 27,800 fatalities and 107,600 hospitalizations, respectively. CONCLUSIONS: Our findings underscore the significance of self-implemented prevention measures by the population and regional NPIs before the national lockdown in Spain. The study also emphasizes the necessity for prompt and precise data quantification prior to enacting enforced measures. This highlights the critical interplay between NPIs, epidemic progression, and human behavior. This interdependence presents a challenge in predicting the impact of NPIs before they are implemented.

Mathematical models of early stage Covid-19 transmission in Sri Lanka: COVID-19 models in Sri Lanka

COVID-19 global pandemic has been significantly damaging the human well-being, life style of people, and the global economy. At the beginning of the epidemic, there were no successful candidates available even though scientists rushed to find one since the start of the official declaration of the pandemic by the World Health Organization (WHO). Thus the countries around the world mostly practiced nonpharmaceutical interventions (NPIs) in various combinations to combat the virus expecting to minimize the public health burden. Since the identification of the first COVID-19 local case on March 11, 2020, the government of Sri Lanka introduced serious social distancing and public health interventions in their fullest capacity as a developing nation to effectively combat the disease spread. These measures had been considerably successful as they contributed to flattening the epidemic curve within two months. However, the nation was at significant risk to the virus due to evolving global epidemic situation, and several clusters of cases have subsequently emerged from a number of jurisdictions in the country. Mathematical models are used to predict the epidemic, to assess the efficacy of public health interventions and social distancing measures recommended by health authorities, to evaluate the national policies to ease lock-down measures in highly affected countries, and the model-based outcomes are extremely useful in various optimal decision-making in public health. Multiple SEIR (Susceptible-Exposed-Infected-Recovered) class models were applied to investigate the early stage of the COVID-19 transmission dynamic in Sri Lanka. These models coupled with optimization techniques were used to estimate the initial transmission rate and the initial epidemic size of the outbreak. A theoretical optimal control problem was developed to identify best allocation of resources in three types of control measures that minimizes the infection in the community. A sensitivity analysis of parameters such as the efficacy of NPIs over the early phase of the outbreak, their timing of implementation, and management of imported overseas cases was carried out mainly addressing their importance in mild and critically ill cases projections. © 2023 Elsevier Inc. All rights reserved.

Unintended Consequences of COVID-19 Non-Pharmaceutical Interventions (NPIs) for Population Health and Health Inequalities.

Since the start of the COVID-19 pandemic in early 2020, governments around the world have adopted an array of measures intended to control the transmission of the SARS-CoV-2 virus, using both pharmaceutical and non-pharmaceutical interventions (NPIs). NPIs are public health interventions that do not rely on vaccines or medicines and include policies such as lockdowns, stay-at-home orders, school closures, and travel restrictions. Although the intention was to slow viral transmission, emerging research indicates that these NPIs have also had unintended consequences for other aspects of public health. Hence, we conducted a narrative review of studies investigating these unintended consequences of NPIs, with a particular emphasis on mental health and on lifestyle risk factors for non-communicable diseases (NCD): physical activity (PA), overweight and obesity, alcohol consumption, and tobacco smoking. We reviewed the scientific literature using combinations of search terms such as 'COVID-19', 'pandemic', 'lockdowns', 'mental health', 'physical activity', and 'obesity'. NPIs were found to have considerable adverse consequences for mental health, physical activity, and overweight and obesity. The impacts on alcohol and tobacco consumption varied greatly within and between studies. The variability in consequences for different groups implies increased health inequalities by age, sex/gender, socioeconomic status, pre-existing lifestyle, and place of residence. In conclusion, a proper assessment of the use of NPIs in attempts to control the spread of the pandemic should be weighed against the potential adverse impacts on other aspects of public health. Our findings should also be of relevance for future pandemic preparedness and pandemic response teams.

Lag-time effects of vaccination on SARS-CoV-2 dynamics in German hospitals and intensive-care units.

Background: The Efficacy and effectiveness of vaccination against SARS-CoV-2 have clearly been shown by randomized trials and observational studies. Despite these successes on the individual level, vaccination of the population is essential to relieving hospitals and intensive care units. In this context, understanding the effects of vaccination and its lag-time on the population-level dynamics becomes necessary to adapt the vaccination campaigns and prepare for future pandemics. Methods: This work applied a quasi-Poisson regression with a distributed lag linear model on German data from a scientific data platform to quantify the effects of vaccination and its lag times on the number of hospital and intensive care patients, adjusting for the influences of non-pharmaceutical interventions and their time trends. We separately evaluated the effects of the first, second and third doses administered in Germany. Results: The results revealed a decrease in the number of hospital and intensive care patients for high vaccine coverage. The vaccination provides a significant protective effect when at least approximately 40% of people are vaccinated, whatever the dose considered. We also found a time-delayed effect of the vaccination. Indeed, the effect on the number of hospital patients is immediate for the first and second doses while for the third dose about 15 days are necessary to have a strong protective effect. Concerning the effect on the number of intensive care patients, a significant protective response was obtained after a lag time of about 15-20 days for the three doses. However, complex time trends, e.g. due to new variants, which are independent of vaccination make the detection of these findings challenging. Conclusion: Our results provide additional information about the protective effects of vaccines against SARS-CoV-2; they are in line with previous findings and complement the individual-level evidence of clinical trials. Findings from this work could help public health authorities efficiently direct their actions against SARS-CoV-2 and be well-prepared for future pandemics.

Data-Driven Estimation of Effectiveness of COVID-19 Non-pharmaceutical Intervention Policies

Non-pharmaceutical Interventions (NPIs), such as Stay-at-Home, and Face-Mask-Mandate, are essential components of the public health response to contain an outbreak like COVID-19. However, it is very challenging to quantify the individual or joint effectiveness of NPIs and their impact on people from different racial and ethnic groups or communities in general. Therefore, in this paper, we study the following two research questions: 1) How can we quantitatively estimate the effectiveness of different NPI policies pertaining to the COVID-19 pandemic?;and 2) Do these policies have considerably different effects on communities from different races and ethnicity? To answer these questions, we model the impact of an NPI as a joint function of stringency and effectiveness over a duration of time. Consequently, we propose a novel stringency function that can provide an estimate of how strictly an NPI was implemented on a particular day. Next, we applied two popular tree-based discriminative classifiers, considering the change in daily COVID cases and death counts as binary target variables, while using stringency values of different policies as independent features. Finally, we interpreted the learned feature weights as the effectiveness of COVID-19 NPIs. Our experimental results suggest that, at the country level, restaurant closures and stay-at-home policies were most effective in restricting the COVID-19 confirmed cases and death cases respectively;and overall, restaurant closing was most effective in hold-down of COVID-19 cases at individual community levels such as Asian, White, Black, AIAN and, NHPI. Additionally, we also performed a comparative analysis between race-specific effectiveness and country-level effectiveness to see whether different communities were impacted differently. Our findings suggest that the different policies impacted communities (race and ethnicity) differently. © 2022 IEEE.

The impact of COVID-19 non-pharmaceutical interventions on HIV care continuum in China: An interrupted time series analysis.

Background: China implemented strict non-pharmaceutical interventions to contain COVID-19 at the early stage. We aimed to evaluate the impact of COVID-19 on HIV care continuum in China. Methods: Aggregated data on HIV care continuum between 1 January 2017 and 31 December 2020 were collected from centers for disease control and prevention at different levels and major infectious disease hospitals in various regions in China. We used interrupted time series analysis to characterize temporal trend in weekly numbers of HIV post-exposure prophylaxis (PEP) prescriptions, HIV tests, HIV diagnoses, median time intervals between HIV diagnosis and antiretroviral therapy (ART) initiation (time intervals, days), ART initiations, mean CD4+ T cell counts at ART initiation (CD4 counts, cells/µL), ART collections, and missed visits for ART collection, before and after the implementation of massive NPIs (23 January to 7 April 2020). We used Poisson segmented regression models to estimate the immediate and long-term impact of NPIs on these outcomes. Findings: A total of 16,780 PEP prescriptions, 1,101,686 HIV tests, 69,659 HIV diagnoses, 63,409 time intervals and ART initiations, 61,518 CD4 counts, 1,528,802 ART collections, and 6656 missed visits were recorded during the study period. The majority of outcomes occurred in males (55·3-87·4%), 21-50 year olds (51·7-90·5%), Southwestern China (38·2-82·0%) and heterosexual transmission (47·9-66·1%). NPIs was associated with 71·5% decrease in PEP prescriptions (IRR 0·285; 95% CI 0·192-0·423), 36·1% decrease in HIV tests (0·639, 0·497-0·822), 32·0% decrease in HIV diagnoses (0·680, 0·511-0·904), 59·3% increase in time intervals (1·593, 1·270-1·997) and 17·4% decrease in CD4 counts (0·826, 0·746-0·915) in the first week during NPIs. There was no marked change in the number of ART initiations, ART collections and missed visits during the NPIs. By the end of 2020, the number of HIV tests, HIV diagnoses, time intervals, ART initiations, and CD4 counts reached expected levels, but the number of PEP prescriptions (0·523, 0·394-0·696), ART collections (0·720, 0·595-0·872), and missed visits (0·137, 0·086-0·220) were still below expected levels. With the ease of restrictions, PEP prescriptions (slope change 1·024/week, 1·012-1·037), HIV tests (1·016/week, 1·008-1·026), and CD4 counts (1·005/week, 1·001-1·009) showed a significant increasing trend. Interpretation: HIV care continuum in China was affected by the COVID-19 NPIs at various levels. Preparedness and efforts to maintain the HIV care continuum during public health emergencies should leverage collaborations between stakeholders. Funding: Natural Science Foundation of China.

A mathematical model reveals the influence of NPIs and vaccination on SARS-CoV-2 Omicron Variant.

An SVEIR SARS-CoV-2 Omicron variant model is proposed to provide some insights to coordinate non-pharmaceutical interventions (NPIs) and vaccination. Mathematically, we define the basic reproduction number R 0 and the effective reproduction number R e to measure the infection potential of Omicron variant and formulate an optimal disease control strategy. Our inversion results imply that the sick period of Omicron variant in the United States is longer than that of Delta variant in India. The decrease in the infectious period of the infection with infectiousness implies that the risk of hospitalization is reduced; but the increasing period of the infection with non-infectiousness signifies that Omicron variant lengthens the period of nucleic acid test being negative. Optimistically, Omicron's death rate is only a quarter of Delta's. Moreover, we forecast that the cumulative cases will exceed 100 million in the United States on February 28, 2022, and the daily confirmed cases will reach a peak on February 2, 2022. The results of parameters sensitivity analysis imply that NPIs are helpful to reduce the number of confirmed cases. In particular, NPIs are indispensable even if all the people were vaccinated when the efficiency of vaccine is relatively low. By simulating the relationships of the effective reproduction number R e , the vaccination rate and the efficacy of vaccine, we find that it is impossible to achieve the herd immunity without NPIs while the efficiency of vaccine is lower than 88.7 % . Therefore, the herd immunity area is defined by the evolution of relationships between the vaccination rate and the efficacy of vaccine. Finally, we present that the disease-induced mortality rate demonstrates the periodic oscillation and an almost periodic function is deduced to match the curve. A discussion completes the paper.

COVID-19 Mass Vaccination and Flu season: Concern for Decreased Public Health Measures and worsening the influenza situation.

Reports show that other ordinary childhood infections like measles or Influenza are likely to reemerge. The re-emergence of infectious diseases may happen due to the direct impact of the pandemic on the community because of decreased access to health and medical services, interrupted transport systems, weaknesses in the supply chain, flight restrictions, closings of the border, and international trade problems. The most prevalent cause [60.9%] for low vaccine uptake and coverage during the current pandemic was fear of exposure to the COVID-19 virus outside the home. The expectation and hope that the pattern of reduction in transmission and number of influenza cases will continue over the next flu season depend on continued adherence to nonpharmaceutical interventions and their long-term application. But there is always the fear and threat of increasing the spread of Influenza by reducing the movement restrictions and low adherence to protective health measures due to vaccination. So far, not much information has been published about the interaction between different infectious diseases in the background of the coronavirus pandemic and related interventions. The purpose of this article is to examine the general effects of the Covid-19 vaccination on the spread of Influenza in the coming seasons.

Bayesian Spatio-Temporal Prediction and Counterfactual Generation: An Application in Non-Pharmaceutical Interventions in COVID-19.

The spatio-temporal course of an epidemic (such as COVID-19) can be significantly affected by non-pharmaceutical interventions (NPIs) such as full or partial lockdowns. Bayesian Susceptible-Infected-Removed (SIR) models can be applied to the spatio-temporal spread of infectious diseases (STIFs) (such as COVID-19). In causal inference, it is classically of interest to investigate the counterfactuals. In the context of STIF, it is possible to use nowcasting to assess the possible counterfactual realization of disease in an incidence that would have been evidenced with no NPI. Classic lagged dependency spatio-temporal IF models are discussed, and the importance of the ST component in nowcasting is assessed. Real examples of lockdowns for COVID-19 in two US states during 2020 and 2021 are provided. The degeneracy in prediction over longer time periods is highlighted, and the wide confidence intervals characterize the forecasts. For SC, the early and short lockdown contrasted with the longer NJ intervention. The approach here demonstrated marked differences in spatio-temporal disparities across counties with respect to an adherence to counterfactual predictions.

The changed endemic pattern of human adenovirus from species B to C among pediatric patients under the pressure of non-pharmaceutical interventions against COVID-19 in Beijing, China.

BACKGROUND: Under the pressure of non-pharmaceutical interventions (NPIs) targeting severe acute respiratory syndrome coronavirus 2, the prevalence of human adenovirus (HAdV) was monitored before and after NPIs launched on Jan 24, 2020 in pediatric patients in Beijing, China. METHODS: Respiratory samples collected from children hospitalized with acute respiratory infections from Jan 2015 to Dec 2021 were screened by direct immunofluorescence test or capillary electrophoresis-based multiplex PCR assay. The hexon, penton base, and fiber genes were amplified from HAdV positive specimens, then sequenced. For HAdV typing, phylogenetic trees were built by MEGA X. Then clinical data of HAdV positive cases were collected. All data were evaluated using SPSS Statistics 22.0 software. RESULTS: A total of 16,097 children were enrolled and 466 (2.89%, 466/16,097) were HAdV-positive. The positive rates of HAdV varied, ranging from 4.39% (151/3,438) in 2018 to1.25% (26/2,081) in 2021, dropped from 3.19% (428/13,408) to 1.41% (38/2,689) from before to after NPIs launched (P < 0.001). There were 350 cases typed into nine types of species B, C, or E and 34 recorded as undetermined. Among them, HAdV-B3 (51.56%, 198/384) was the most prevalent types from 2015 to 2017, and HAdV-B7 (29.17%, 112/384) co-circulated with HAdV-B3 from 2018 to 2019. After NPIs launched, HAdV-B3 and B7 decreased sharply with HAdV-B7 undetected in 2021, while HAdV-C1 became the dominant one and the undetermined were more. CONCLUSIONS: The endemic pattern of HAdV changed in Beijing because of the NPIs launched for COVID-19. Especially, the dominant types changed from HAdV-B to HAdV-C.

Exploring meteorological impacts based on Köppen-Geiger climate classification after reviewing China's response to COVID-19.

More than 30 months into the novel coronavirus 2019 (COVID-19) pandemic, efforts to bring this prevalence under control have achieved tentative achievements in China. However, the continuing increase in confirmed cases worldwide and the novel variants imply a severe risk of imported viruses. High-intensity non-pharmaceutical interventions (NPIs) are the mainly used measures of China's early response to COVID-19, which enabled effective control in the first wave of the epidemic. However, their efficiency is relatively low across China at the current stage. Therefore, this study focuses on whether measurable meteorological variables be found through global data to learn more about COVID-19 and explore flexible controls. This study first examines the control measures, such as NPIs and vaccination, on COVID-19 transmission across 189 countries, especially in China. Subsequently, we estimate the association between meteorological factors and time-varying reproduction numbers based on the global data by meta-population epidemic model, eliminating the aforementioned anthropogenic factors. According to this study, we find that the basic reproduction number of COVID-19 transmission varied wildly among Köppen-Geiger climate classifications, which is of great significance for the flexible adjustment of China's control protocols. We obtain that in southeast China, Köppen-Geiger climate sub-classifications, Cwb, Cfa, and Cfb, are more likely to spread COVID-19. In August, the RSIM of Cwb climate subclassification is about three times that of Dwc in April, which implies that the intensity of control efforts in different sub-regions may differ three times under the same imported risk. However, BSk and BWk, the most widely distributed in northwest China, have smaller basic reproduction numbers than Cfa, distributed in southeast coastal areas. It indicates that northwest China's control intensity could be appropriately weaker than southeast China under the same prevention objectives.

Using interpretable machine learning identify factors contributing to COVID-19 cases in the United States

COVID-19 has been declared as a “pandemic” by the World Health Organization (WHO) and has claimed more than a million lives and over 50 million confirmed cases worldwide as of 7th November 2020. This virus can be curbed in only two ways: vaccination and other by imposing non-pharmaceutical interventions (NPIs), which are behavioral changes to a person and community. Most of the nations worldwide have imposed NPIs in the form of social distancing and lockdowns, which have been effective in reducing the pace of the virus's spread, but continued implementation has deemed social and economic losses. Hence strategic implementation of NPIs in a burst of periods should be done based on educated decisions using data about population mobility trends to find hot zones that lead to a spike in cases. These decisions will positively impact the virus's spread with lower damage to social and economic aspects. © 2022 Elsevier Inc. All rights reserved.

Non-pharmaceutical interventions and their relevance in the COVID-19 vaccine rollout in Saudi Arabia and Arab Gulf countries.

In the early stages of the pandemic, Saudi Arabia and other countries in the Arab Gulf region relied on non-pharmaceutical therapies to limit the effect of the pandemic, much like other nations across the world. In comparison to other nations in the area or globally, these interventions were successful at lowering the healthcare burden. This was accomplished via the deterioration of the economy, education, and a variety of other societal activities. By the end of 2020, the promise of effective vaccinations against SARS-CoV-2 have been realized, and vaccination programs have begun in developed countries, followed by the rest of the world. Despite this, there is still a long way to go in the fight against the disease. In order to explore disease transmission, vaccine rollout and prioritisation, as well as behavioural dynamics, we relied on an age-structured compartmental model. We examine how individual and social behaviour changes in response to the initiation of vaccination campaigns and the relaxation of non-pharmacological treatments. Overall, vaccination remains the most effective method of containing the disease and resuming normal life. Additionally, we evaluate several vaccination prioritisation schemes based on age group, behavioural responses, vaccine effectiveness, and vaccination rollout speed. We applied our model to four Arab Gulf nations (Saudi Arabia, Bahrain, the United Arab Emirates, and Oman), which were chosen for their low mortality rate compared to other countries in the region or worldwide, as well as their demographic and economic settings. We fitted the model using actual pandemic data in these countries. Our results suggest that vaccinations focused on the elderly and rapid vaccine distribution are critical for reducing disease resurgence. Our result also reinforces the cautious note that early relaxation of safety measures may compromise the vaccine's short-term advantages.

Unemployment claims during COVID-19 and economic support measures in the U.S.

Governments want to know how effective COVID-19 anti-contagion policies and implemented economic stimulus measures have been to plan their short-run interventions. We condition on the state of the pandemic to assess the impact of non-pharmaceutical interventions and economic stimulus policies on the excess unemployment insurance claims in the United States. We focus on weekly data between February 2020 and January 2021 and motivate our analysis by the theoretical framework of the second-wave SIR-macro type models to build a panel Vector AutoRegressive (VAR) specification. Non-pharmaceutical interventions become effective immediately and impact the labor market negatively. Economic stimulus takes about a month to turn effective and only partially eases the economic welfare losses. Health-related restrictive measures are primarily driven by the state of the pandemic. Economic support policies depend predominantly on the reaction of the labor market rather than the severity of the pandemic itself.

The cross-over of statistical thinking and practices: A pandemic catalyst.

Written during the SARS-CoV-2 pandemic, and in recognition of Andy Grieve, the polymath, this article looks at an eclectic mix of topics where statistical thinking and practices should transcend typical dividing lines-with a particular focus on the areas of drug development, public health and social science. The case is made for embedding an experimental (or quasi-experimental) framework within clinical practice for vaccines and treatments following their marketing authorisation. A similar case is made for public health interventions-facilitated by pre-specification of effect size and by the greater use of data standards. A number of recommendations are made whilst noting that progress is being made in some areas.

Comparison of COVID-19 Resilience Index and Its Associated Factors across 29 Countries during the Delta and Omicron Variant Periods.

Our study aims to compare the pandemic resilience index and explore the associated factors during the Delta and Omicron variant periods. In addition, the study aims to identify the characteristics of countries that had good performances. We analyzed observation data among 29 countries over the first eight weeks during the two periods of Delta and Omicron variant dominance. Data were extracted from open public databases. The Omicron variant caused a lowered mortality rate per 100,000 COVID-19 patients; however, it is still imposing a colossal burden on health care systems. We found the percentage of the population fully vaccinated and high government indices were significantly associated with a better resilience index in both the Delta and Omicron periods. In contrast, the higher death rate of cancers and greater years lived with disability (YLD) caused by low bone density were linked with poor resilience index in the Omicron periods. Over two periods of Delta and Omicron, countries with good performance had a lower death rate from chronic diseases and lower YLD caused by nutrition deficiency and PM2.5. Our findings suggest that governments need to keep enhancing the vaccine coverage rates, developing interventions for populations with chronic diseases and nutrition deficiency to mitigate COVID-19 impacts on these targeted vulnerable cohorts.

Was the Reduction in Seasonal Influenza Transmission during 2020 Attributable to Non-Pharmaceutical Interventions to Contain Coronavirus Disease 2019 (COVID-19) in Japan?

We quantified the effects of adherence to various non-pharmaceutical interventions (NPIs) on the seasonal influenza epidemic dynamics in Japan during 2020. The total monthly number of seasonal influenza cases per sentinel site (seasonal influenza activity) reported to the National Epidemiological Surveillance of Infectious Diseases and alternative NPI indicators (retail sales of hand hygiene products and number of airline passenger arrivals) from 2014-2020 were collected. The average number of monthly seasonal influenza cases in 2020 had decreased by approximately 66.0% (p < 0.001) compared to those in the preceding six years. An increase in retail sales of hand hygiene products of ¥1 billion over a 3-month period led to a 15.5% (95% confidence interval [CI]: 10.9-20.0%; p < 0.001) reduction in seasonal influenza activity. An increase in the average of one million domestic and international airline passenger arrivals had a significant association with seasonal influenza activity by 11.6% at lag 0-2 months (95% CI: 6.70-16.5%; p < 0.001) and 30.9% at lag 0-2 months (95% CI: 20.9-40.9%; p < 0.001). NPI adherence was associated with decreased seasonal influenza activity during the COVID-19 pandemic in Japan, which has crucial implications for planning public health interventions to minimize the health consequences of adverse seasonal influenza epidemics.