Impact of climate and public health interventions on the COVID-19 pandemic: a prospective cohort study

A data-driven analysis on the mediation effect of compartment models between control measures and COVID-19 epidemics

By collecting various control policies taken by 127 countries/territories during the first wave of COVID-19 pandemic until July 2nd, 2020, we evaluate their impacts on the epidemic dynamics quantitatively through a combination of the multiple linear regression, neural-network-based nonlinear regression and sensitivity analysis. Remarkable differences in the public health policies are observed across these countries, which affect the spreading rate and infected population size to a great extent. Several key dynamical features, like the normalized cumulative numbers of confirmed/cured/death cases on the 100th day and the half time, show statistically significant linear correlations with the control measures, which thereby confirms their dramatic impacts. Most importantly, we perform the mediation analysis on the SEIR-QD model, a representative of general compartment models, by using the structure equation modeling for multiple mediators operating in parallel. This, to the best of our knowledge, is the first of its kind in the field of epidemiology. The infection rate and the protection rate of the SEIR-QD model are confirmed to exhibit a statistically significant mediation effect between the control measures and dynamical features of epidemics. The mediation effect along the pathway from control measures in Category 2 to four dynamical features through the infection rate, highlights the crucial role of nucleic acid testing and suspected cases tracing in containing the spread of the epidemic. Our data-driven analysis offers a deeper insight into the inherent correlations between the effectiveness of public health policies and the dynamic features of COVID-19 epidemics.

Self-reported chronic conditions and COVID-19 public health measures among Canadian adults: an analysis of the Canadian longitudinal study on aging

OBJECTIVES

During the COVID-19 pandemic, public health measures were used to reduce the spread of COVID-19; it is unknown whether people with chronic conditions differentially adhered to public health measures. The objectives of this study were to evaluate the association between chronic conditions and adherence and to explore effect modification by sex, age, and income.

STUDY DESIGN

An analysis of data from the Canadian Longitudinal Study on Aging COVID-19 Questionnaires (from April to September 2020) was conducted among middle-aged and older adults aged 50-96 years (n = 28,086).

METHODS

Self-reported chronic conditions included lung disease, diabetes, heart disease, cancer, obesity, anxiety, and depression. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between chronic conditions and low, medium, and high levels of adherence. Effect modification was evaluated using statistical interaction and stratification.

RESULTS

Most people (n = 17,435; 62%) had at least one chronic condition, and 2866 (10%) had three to seven chronic conditions. Among those with high adherence to public health measures, 69% had one or more chronic condition (n = 2266). Having three to seven chronic conditions, compared with none, was associated with higher adherence to public health measures (OR: 2.14; 95% CI: 1.12-1.42). Higher adherence was also noted across chronic conditions, for example, those with diabetes had higher adherence (OR: 1.72; 95% CI: 1.53-1.93). There was limited evidence of effect modification by sex, age, or income.

CONCLUSIONS

Canadians with chronic conditions were more likely to adhere to public health measures; however, future research is needed to understand whether adherence helped to prevent adverse COVID-19 outcomes and if adherence had unintended consequences.

Compound mortality impacts from extreme temperatures and the COVID-19 pandemic

Extreme weather and coronavirus-type pandemics are both leading global health concerns. Until now, no study has quantified the compound health consequences of the co-occurrence of them. We estimate the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality. We show that temperature-related mortality exceeded COVID-19 mortality by 8% in South West England. Combined, extreme temperatures and COVID-19 led to 19 (95% confidence interval: 16-22 in North West England) to 24 (95% confidence interval: 20-29 in Wales) excess deaths per 100,000 population during heatwaves, and 80 (95% confidence interval: 75-86 in Yorkshire and the Humber) to 127 (95% confidence interval: 123-132 in East of England) excess deaths per 100,000 population during cold snaps. These numbers are at least ~2 times higher than the previous decade. Society must increase preparedness for compound health crises such as extreme weather coinciding with pandemics.

Persistence and Variation of the Indirect Effects of COVID-19 Restrictions on the Spectrum of Notifiable Infectious Diseases in China: Analysis of National Surveillance Among Children and Adolescents From 2018 to 2021

BACKGROUND

Beyond the direct effect of COVID-19 infection on young people, the wider impact of the pandemic on other infectious diseases remains unknown.

OBJECTIVE

This study aims to assess changes in the incidence and mortality of 42 notifiable infectious diseases during the pandemic among children and adolescents in China, compared with prepandemic levels.

METHODS

The Notifiable Infectious Disease Surveillance System of China was used to detect new cases and fatalities among individuals aged 5-22 years across 42 notifiable infectious diseases spanning from 2018 to 2021. These infectious diseases were categorized into 5 groups: respiratory, gastrointestinal and enterovirus, sexually transmitted and blood-borne, zoonotic, and vector-borne diseases. Each year (2018-2021) was segmented into 4 phases: phase 1 (January 1-22), phase 2 (January 23-April 7), phase 3 (April 8-August 31), and phase 4 (September 1-December 31) according to the varying intensities of pandemic restrictive measures in 2020. Generalized linear models were applied to assess the change in the incidence and mortality within each disease category, using 2018 and 2019 as the reference.

RESULTS

A total of 4,898,260 incident cases and 3701 deaths were included. The overall incidence of notifiable infectious diseases decreased sharply during the first year of the COVID-19 pandemic (2020) compared with prepandemic levels (2018 and 2019), and then rebounded in 2021, particularly in South China. Across the past 4 years, the number of deaths steadily decreased. The incidence of diseases rebounded differentially by the pandemic phase. For instance, although seasonal influenza dominated respiratory diseases in 2019, it showed a substantial decline during the pandemic (percent change in phase 2 2020: 0.21, 95% CI 0.09-0.50), which persisted until 2021 (percent change in phase 4 2021: 1.02, 95% CI 0.74-1.41). The incidence of gastrointestinal and enterovirus diseases decreased by 33.6% during 2020 but rebounded by 56.9% in 2021, mainly driven by hand, foot, and mouth disease (percent change in phase 3 2021: 1.28, 95% CI 1.17-1.41) and infectious diarrhea (percent change in phase 3 2020: 1.22, 95% CI 1.17-1.28). Sexually transmitted and blood-borne diseases were restrained during the first year of 2021 but rebounded quickly in 2021, mainly driven by syphilis (percent change in phase 3 2020: 1.31, 95% CI 1.23-1.40) and gonorrhea (percent change in phase 3 2020: 1.10, 95% CI 1.05-1.16). Zoonotic diseases were not dampened by the pandemic but continued to increase across the study period, mainly due to brucellosis (percent change in phase 2 2020: 0.94, 95% CI 0.75-1.16). Vector-borne diseases showed a continuous decline during 2020, dominated by hemorrhagic fever (percent change in phase 2 2020: 0.68, 95% CI 0.53-0.87), but rebounded in 2021.

CONCLUSIONS

The COVID-19 pandemic was associated with a marked decline in notifiable infectious diseases in Chinese children and adolescents. These effects were not sustained, with evidence of a rebound to prepandemic levels by late 2021. To effectively address the postpandemic resurgence of infectious diseases in children and adolescents, it will be essential to maintain disease surveillance and strengthen the implementation of various initiatives. These include extending immunization programs, prioritizing the management of sexually transmitted infections, continuing feasible nonpharmaceutical intervention projects, and effectively managing imported infections.

Evaluating the Effectiveness of Public Health Measures During Infectious Disease Outbreaks: A Systematic Review

Over the previous three decades, the incidence of infectious disease outbreaks has considerably increased and the trend is expected to increase further. Public health measures are essential for controlling and preventing emerging outbreaks of infectious illnesses. This study is aimed at evaluating the effectiveness of public health measures during infectious disease outbreaks by summarizing the outcomes from the available evidence in the literature. A systematic review was carried out through a detailed search strategy using specific keywords applied across different electronic databases, including the Science Direct, PubMed, and EMBASE databases. Studies published between 2015 and 2024 were included with a focus on cohorts, clinical trials, longitudinal studies, case-control, and quasi-experimental studies. Low-quality studies and those published before 2015 along with incorrect findings or measures were excluded. A standardized form was used for data extraction. The quality of included studies and the risk of bias were assessed through relevant techniques. The obtained data was narrative synthesized and findings were organized systematically. The reviewed studies revealed that public health measures are considerably effective against infectious disease outbreaks. The success of various measures such as social isolation, confinement measures, and public education on hygiene against different outbreaks of respiratory infectious diseases has been well-established in the literature. Moreover, the timing of intervention application plays a vital role in their success. The implementation in the early phase of an outbreak is highly effective, as it protects more people from infection and controls the overall burden of the disease. The systematic review provided valuable insights into the efficiency of public health measures in monitoring outbreaks of infectious illnesses. The main findings suggest that appropriate public health interventions are effective in controlling the incidence of contagious disease outbreaks. Ongoing research strives to investigate measures that are most effective from the perspective of public health against various transmittable diseases to prevent future outbreaks.

Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe

BACKGROUND

Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined the contribution of these three factors to the progression of the COVID-19 pandemic.

METHODS

Pearson correlation coefficients and time-lagged analysis were used to examine the relationship between NPIs, vaccinations and seasonality (using the average incidence of endemic human beta-coronaviruses in Sweden over a 10-year period as a proxy) and the progression of the COVID-19 pandemic as tracked by deaths; cases; hospitalisations; intensive care unit occupancy and testing positivity rates in six Northern European countries (population 99.12 million) using a population-based, observational, ecological study method.

FINDINGS

The waves of the pandemic correlated well with the seasonality of human beta-coronaviruses (HCoV-OC43 and HCoV-HKU1). In contrast, we could not find clear or consistent evidence that the stringency of NPIs or vaccination reduced the progression of the pandemic. However, these results are correlations and not causations.

IMPLICATIONS

We hypothesise that the apparent influence of NPIs and vaccines might instead be an effect of coronavirus seasonality. We suggest that policymakers consider these results when assessing policy options for future pandemics.

LIMITATIONS

The study is limited to six temperate Northern European countries with spatial and temporal variations in metrics used to track the progression of the COVID-19 pandemic. Caution should be exercised when extrapolating these findings.

Association of Ambient Temperature and Absolute Humidity with the Effective Reproduction Number of COVID-19 in Japan

This study aimed to quantify the exposure-lag-response relationship between short-term changes in ambient temperature and absolute humidity and the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Japan. The prefecture-specific daily time-series of newly confirmed cases, meteorological variables, retail and recreation mobility, and Government Stringency Index were collected for all 47 prefectures of Japan for the study period from 15 February 2020 to 15 October 2022. Generalized conditional Gamma regression models were formulated with distributed lag nonlinear models by adopting the case-time-series design to assess the independent and interactive effects of ambient temperature and absolute humidity on the relative risk (RR) of the time-varying effective reproductive number (Rt). With reference to 17.8 °C, the corresponding cumulative RRs (95% confidence interval) at a mean ambient temperatures of 5.1 °C and 27.9 °C were 1.027 (1.016-1.038) and 0.982 (0.974-0.989), respectively, whereas those at an absolute humidity of 4.2 m/g3 and 20.6 m/g3 were 1.026 (1.017-1.036) and 0.995 (0.985-1.006), respectively, with reference to 10.6 m/g3. Both extremely hot and humid conditions synergistically and slightly reduced the Rt. Our findings provide a better understanding of how meteorological drivers shape the complex heterogeneous dynamics of SARS-CoV-2 in Japan.

Climate and COVID-19 transmission: a cross-sectional study in Africa

The role of climate in the Coronavirus disease 2019 (COVID-19) transmission appears to be controversial, as reported in earlier studies. In Africa, the subject is poorly documented. In this study, over the period from January 1st, 2020 to September 31, 2022, the daily variations in cumulative confirmed cases of COVID-19 for each African country (54 countries) are modelled through time-series-based approaches and using meteorological factors as covariates. It is suggested from the findings that climate plays a role in COVID-19 transmission since at least one meteorological factor is found to be significant in 32 countries. In decreasing order, the most often occurring meteorological factors are dewpoint temperature, relative and absolute humidity, average temperature and solar radiation. Most of these factors show a lagged effect with confirmed cases (between 0 and 28 days). Also, some meteorological factors exhibit contrasting effects on COVID-19 transmission, resulting in both positive and negative association with cumulative cases, therefore highlighting the complex nature of the interplay between climate and COVID-19 transmission.

Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings

Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.

To open or not to open: the moderating effects of human mobility on the relationship between vaccination and COVID-19 transmission

COVID-19 vaccination is being used to control SARS-CoV-2 transmission globally, and many countries have relaxed some non-pharmaceutical interventions. It is unclear whether relaxing human mobility restrictions is proper and increases transmission risk. To fill this knowledge gap, we aim to examine if human mobility impairs the role of vaccination on COVID-19 transmission. We apply dynamic panel data models with three lag levels (i.e. 0 day, 7 days, and 14 days) to investigate the relationship between vaccination and COVID-19 transmission and the moderating effects of different kinds of human mobility. Our results show a negative relationship between the percentage of the vaccinated population and daily new COVID-19 cases after controlling for human mobility. We also observe that when people are only vaccinated with one dose, increased human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, and workplaces could impair the role of vaccination on COVID-19 transmission, although their moderating effects appear at different lag levels. However, there are no moderating effects of human mobility in transit stations and workplaces at all lag levels when people are fully vaccinated. This finding does not mean that governments may relax restrictions in these two areas since mobility in transit stations and workplaces could affect COVID-19 transmission by themselves directly. Therefore, we recommend that governments still insist on implementing human mobility control measures from the perspective of transmission risk.

Utilizing nanozymes for combating COVID-19: advancements in diagnostics, treatments, and preventative measures

The emergence of human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses significant challenges to global public health. Despite the extensive efforts of researchers worldwide, there remains considerable opportunities for improvement in timely diagnosis, specific treatment, and effective vaccines for SARS-CoV-2. This is due, in part, to the large number of asymptomatic carriers, rapid virus mutations, inconsistent confinement policies, untimely diagnosis and limited clear treatment plans. The emerging of nanozymes offers a promising approach for combating SARS-CoV-2 due to their stable physicochemical properties and high surface areas, which enable easier and multiple nano-bio interactions in vivo. Nanozymes inspire the development of sensitive and economic nanosensors for rapid detection, facilitate the development of specific medicines with minimal side effects for targeted therapy, trigger defensive mechanisms in the form of vaccines, and eliminate SARS-CoV-2 in the environment for prevention. In this review, we briefly present the limitations of existing countermeasures against coronavirus disease 2019 (COVID-19). We then reviewed the applications of nanozyme-based platforms in the fields of diagnostics, therapeutics and the prevention in COVID-19. Finally, we propose opportunities and challenges for the further development of nanozyme-based platforms for COVID-19. We expect that our review will provide valuable insights into the new emerging and re-emerging infectious pandemic from the perspective of nanozymes.

What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update

The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.

Impact of combination preventative interventions on hospitalization and death under the pandemic of SARS-CoV-2 Omicron variant in China

With a large population most susceptible to Omicron and emerging SARS-CoV-2 variants, China faces uncertain scenarios if reopening its border. Thus, we aimed to predict the impact of combination preventative interventions on hospitalization and death. An age-stratified susceptible-infectious-quarantined-hospitalized-removed-susceptible (SIQHRS) model based on the new guidelines of COVID-19 diagnosis and treatment (the ninth edition) was constructed to simulate the transmission dynamics of Omicron within 365 days. At baseline, we assumed no interventions other than 60% booster vaccination in individuals aged ≤60 years and 80% in individuals aged >60 years, quarantine and hospitalization. Oral antiviral medications for COVID-19 and nonpharmaceutical interventions (NPIs) such as social distancing and antigen self-testing were considered in subsequent scenarios. Sensitivity analyses were conducted to reflect different levels of interventions. A total of 0.73 billion cumulative quarantines (95% CI 0.53-0.83), 33.59 million hospitalizations (22.41-39.31), and 0.62 million deaths (0.40-0.75) are expected in 365 days. The case fatality rate with pneumonia symptoms (moderate, severe and critical illness) is expected to be 1.83% (1.68-1.99%) and the infected fatality rate is 0.38‰ (0.33-0.4‰). The highest existing hospitalization and ICU occupations are 3.11 (0.30-3.85) and 20.33 (2.01-25.20) times of capacity, respectively. Sensitivity analysis showed that interventions can be adjusted to meet certain conditions to reduce the total number of infections and deaths. In conclusion, after sufficient respiratory and ICU beds are prepared and the relaxed NPIs are in place, the SARS-CoV-2 Omicron variant would not seriously impact the health system.

Comparison of health-oriented cross-regional allocation strategies for the COVID-19 vaccine: a mathematical modelling study

BACKGROUND

Controlling the epidemic spread and establishing the immune barrier in a short time through accurate vaccine demand prediction and optimised vaccine allocation strategy are still urgent problems to be solved under the condition of frequent virus mutations.

METHODS

A cross-regional Susceptible-Exposed-Infected-Removed dynamic model was used for scenario simulation to systematically elaborate and compare the effects of different cross-regional vaccine allocation strategies on the future development of the epidemic in regions with different population sizes, prevention and control capabilities, and initial risk levels. Furthermore, the trajectory of the cross-regional vaccine allocation strategy, calculated using a particle swarm optimisation algorithm, was compared with the trajectories of other strategies.

RESULTS

By visualising the final effect of the particle swarm optimisation vaccine allocation strategy, this study revealed the important role of prevention and control (including the level of social distancing control, the speed of tracking and isolating exposed and infected individuals, and the initial frequency of mask-wearing) in determining the allocation of vaccine resources. Most importantly, it supported the idea of prioritising control in regions with a large population and low initial risk level, which broke the general view that high initial risk needs to be given priority and proposed that outbreak risk should be firstly considered instead.

CONCLUSIONS

This is the first study to use a particle swarm optimisation algorithm to study the cross-regional allocation of COVID-19 vaccines. These data provide a theoretical basis for countries and regions to develop more targeted and sustainable vaccination strategies.KEY MESSAGEThe innovative combination of particle swarm optimisation and cross-regional SEIR model to simulate the pandemic trajectory and predict the vaccine demand helped to speed up and stabilise the construction of the immune barrier, especially faced with new virus mutations.We proposed that priority should be given to regions where it is possible to prevent more infections rather than regions where it is at high initial risk, thus regional outbreak risk should be considered when making vaccine allocation decisions.An optimal health-oriented strategy for vaccine allocation in the COVID-19 pandemic is determined considering both pharmaceutical and non-pharmaceutical policy interventions, including speed of isolation, degree of social distancing control, and frequency of mask-wearing.

The global evolution of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis of longitudinal studies

BACKGROUND

The COVID-19 pandemic impacted mental health, but the global evolution of mental health problems during the pandemic is unknown. We conducted a systematic review and meta-analysis of longitudinal studies to evaluate the global evolution of mental health problems during the pandemic.

METHODS

To conduct this systematic review, we searched for published articles from APA PsycInfo (Ovid), CINAHL (EBSCOhost), Embase (Ovid), MEDLINE (Ovid), and Web of Science. Longitudinal (at least 2 waves during the COVID-19 pandemic) and peer-reviewed articles on mental health problems conducted as from 2020 and after were included in the current study. Of 394 eligible full texts, 64 articles were included in the analysis. We computed random effects, standardized mean differences, and log odds ratio (LOR) with 95 % CIs. The meta-analysis protocol was registered with PROSPERO (CRD42021273624).

RESULTS

Results showed that anxiety (LOR = -0.33; 95 % CI, -0.54, -0.12) and depression symptoms (LOR = -0.12; 95 % CI, -0.21, -0.04) decreased from baseline to follow up. However, other mental health problems showed no change. Higher prevalence rates (40.9 %; 95 % CI, 16.1 %-65.8 %) of psychological distress were found in months after July 2020, respectively, while there were no significant month differences for the prevalence of other mental health problems. Higher means of anxiety (d = 3.63, 95 % CI, 1.66, 5.61), depression (d = 3.93; 95 % CI, 1.68, 6.17), and loneliness (d = 5.96; 95 % CI, 3.22, 8.70) were observed in May 2020. Higher prevalence of anxiety, depression, and PTSD and higher means of anxiety, depression and loneliness were observed in North America. The prevalence of psychological distress and insomnia was higher in Latin America and Europe, respectively.

LIMITATIONS

There is a lack of longitudinal studies in some parts of the world, such as Africa, the Caribbean, India, the Middle East, in Latin America, and Asia.

CONCLUSIONS

Results indicated that anxiety and depression symptoms decreased during the COVID-19 pandemic while other mental health problems showed no statistical change. The findings reveal that mental health problems peaked in April and May 2020. Prevalence of mental health problems remains high during the pandemic and mental health prevention, promotion and intervention programs should be implemented to mitigate the consequences of the COVID-19 pandemic on the global population.

Knowledge of Teenagers and Young Adults about COVID-19 and Compliance with Social Distancing Guidelines

OBJECTIVES

Understanding the coronavirus disease 2019 (COVID-19) knowledge and personal preventive behaviors of younger individuals is important as it can affect not only their own health but also the health of other potentially more vulnerable individuals. The aims of this study were to explore the knowledge of teenagers and young adults about COVID-19 and assess their personal preventive behavior.

METHODS

We developed a 14-item questionnaire to conduct a cross-sectional online survey. Survey responses with missing variables were excluded. SPSS was used to perform the analyses, including descriptive statistics.

RESULTS

Thirty-five participants, 15 to 27 years of age, completed the survey between May 2020 and March 2021. Thirty-one (88.57%) reported feeling sufficiently informed to avoid the risk of COVID-19 transmission. The most frequent sources of COVID-19 information were social media (68.6%) and parents (68.6%), whereas the least were teachers (11.4%). Thirty-three (94.29%) participants reported practicing social distancing, citing the main reasons to keep oneself, family members, and others safe. Thirty-three (94.29%) identified taking classes online instead of going to school as an example of social distancing, 26 (74.29%) calling friends on the telephone, and 24 (68.57%) going on a walk alone. Twelve (34.29%) chose eating infected foods and 8 (22.86%) touching animals, including pets, as transmission means for COVID-19. When asked about COVID-19 prevention, 34 (97.14%) reported that COVID-19 can be prevented by avoiding close contact with people who are sick, 31 (88.57%) by covering coughs and sneezes with a tissue, and 8 (22.86%) by avoiding contact with animals, including pets.

CONCLUSIONS

We found high awareness of COVID-19, but also identified important knowledge gaps about COVID-19 and preventive measures. Digital platforms and social media campaigns can be important sources for providing evidence-based and age-appropriate information about COVID-19 and recommendations for safe activities to reduce social isolation during the pandemic and its negative mental health effects. This study also suggests that teachers may be an underused source of accurate information about COVID-19. These findings can be used to develop effective educational interventions to help combat the COVID-19 pandemic and its impact on young individuals.

Does climate help modeling COVID-19 risk and to what extent?

A growing number of studies suggest that climate may impact the spread of COVID-19. This hypothesis is supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data. However, the extent to which climate may affect COVID-19 transmission rates and help modeling COVID-19 risk is still not well understood. This study demonstrates that such an understanding is attainable through the development of regression models that verify how climate contributes to modeling COVID-19 transmission, and the use of feature importance techniques that assess the relative weight of meteorological variables compared to epidemiological, socioeconomic, environmental, and global health factors. The ensuing results show that meteorological factors play a key role in regression models of COVID-19 risk, with ultraviolet radiation (UV) as the main driver. These results are corroborated by statistical correlation analyses and a panel data fixed-effect model confirming that UV radiation coefficients are significantly negatively correlated with COVID-19 transmission rates.

The Relative Contribution of Climatic, Demographic Factors, Disease Control Measures and Spatiotemporal Heterogeneity to Variation of Global COVID-19 Transmission

Despite a substantial number of COVID-19 related research papers published, it remains unclear as to which factors are associated with the observed variation in global transmission and what are their relative levels of importance. This study applies a rigorous statistical framework to provide robust estimations of the factor effects for a global and integrated perspective on this issue. We developed a mixed effect model exploring the relative importance of potential factors driving COVID-19 transmission while incorporating spatial and temporal heterogeneity of spread. We use an integrated data set for 87 countries across six continents for model specification and fitting. The best model accounts for 70.4% of the variance in the data analyzed: 10 fixed effect factors explain 20.5% of the variance, random temporal and spatial effects account for 50% of the variance. The fixed effect factors are classified into climatic, demographic and disease control groups. The explained variance in global transmission by the three groups are 0.6%, 1.1%, and 4.4% respectively. The high proportion of variance accounted for by random effects indicated striking differences in temporal transmission trajectories and effects of population mobility among the countries. In particular, the country-specific mobility-transmission relationship turns out to be the most important factor in explaining the observed global variation of transmission in the early phase of COVID-19 pandemic.

Assessment of COVID-19 risk and prevention effectiveness among spectators of mass gathering events

There is a need to evaluate and minimize the risk of novel coronavirus infections at mass gathering events, such as sports. In particular, to consider how to hold mass gathering events, it is important to clarify how the local infection prevalence, the number of spectators, the capacity proportion, and the implementation of preventions affect the infection risk. In this study, we used an environmental exposure model to analyze the relationship between infection risk and infection prevalence, the number of spectators, and the capacity proportion at mass gathering events in football and baseball games. In addition to assessing risk reduction through the implementation of various preventive measures, we assessed how face-mask-wearing proportion affects infection risk. Furthermore, the model was applied to estimate the number of infectors who entered the stadium and the number of newly infected individuals, and to compare them with actual reported cases. The model analysis revealed an 86-95% reduction in the infection risk due to the implementation of face-mask wearing and hand washing. Under conditions in which vaccine effectiveness was 20% and 80%, the risk reduction rates of infection among vaccinated spectators were 36% and 96%, respectively. Among the individual measures, face-mask wearing was particularly effective, and the infection risk increased as the face-mask-wearing proportion decreased. A linear relationship was observed between infection risk at mass gathering events and the infection prevalence. Furthermore, the number of newly infected individuals was also dependent on the number of spectators and the capacity proportion independent of the infection prevalence, confirming the importance of considering spectator capacity in infection risk management. These results highlight that it is beneficial for organisers to ensure prevention compliance and to mitigate or limit the number of spectators according to the prevalence of local infection. Both the estimated and reported numbers of newly infected individuals after the events were small, below 10 per 3-4 million spectators, despite a small gap between these numbers.

Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis

In 2020 North Italy suffered the SARS-CoV-2-related pandemic with a high number of deaths and hospitalization. The effect of atmospheric parameters on the amount of hospital admissions (temperature, solar radiation, particulate matter, relative humidity and wind speed) is studied through about 8 months (May-December). Two periods are considered depending on different conditions: a) low incidence of COVID-19 and very few regulations concerning personal mobility and protection ("free/summer period"); b) increasing incidence of disease, social restrictions and use of personal protections ("confined/autumn period"). The "hospitalized people in medical area wards/100000 residents" was used as a reliable measure of COVID-19 spreading and load on the sanitary system. We developed a chemometric approach (multiple linear regression analysis) using the daily incidence of hospitalizations as a function of the single independent variables and of their products (interactions). Eight administrative domains were considered (altogether 26 million inhabitants) to account for relatively homogeneous territorial and social conditions. The obtained models very significantly match the daily variation of hospitalizations, during the two periods. Under the confined/autumn period, the effect of non-pharmacologic measures (social distances, personal protection, etc.) possibly attenuates the virus diffusion despite environmental factors. On the contrary, in the free/summer conditions the effects of atmospheric parameters are very significant through all the areas. Particulate matter matches the growth of hospitalizations in areas with low chronic particulate pollution. Fewer hospitalizations strongly correspond to higher temperature and solar radiation. Relative humidity plays the same role, but with a lesser extent. The interaction between solar radiation and high temperature is also highly significant and represents surprising evidence. The solar radiation alone and combined with high temperature exert an anti-SARS-CoV-2 effect, via both the direct inactivation of virions and the stimulation of vitamin D synthesis, improving immune system function.

Pandemic wave trends in COVID-19 cases, mobility reduction, and climate parameters in major metropolitan areas in the United States

In this paper, we analyzed the association among trends in COVID-19 cases, climate, air quality, and mobility changes during the first and second waves of the pandemic in five major metropolitan counties in the United States: Maricopa in Arizona, Cook in Illinois, Los Angeles in California, Suffolk in Massachusetts, and New York County in New York. These areas represent a range of climate conditions, geographies, economies, and state-mandated social distancing restrictions. In the first wave of the pandemic, cases were correlated with humidity in Maricopa, and temperature in Maricopa and Los Angeles. In Suffolk and New York, cases were correlated with mobility changes in recreation, grocery, parks, and transit stations. Neither cases nor death counts were strongly correlated with air quality. Periodic fluctuations in mobility were observed for residential areas during weekends, resulting in stronger correlation coefficients when only weekday datasets were included in the analysis. We also analyzed case-mobility correlations when mobility days were lagged, and found that the strongest correlation in the first wave occurred between 12 and 14 lag days (optimal at 13 days). There was stronger but greater variability in correlation coefficients across metropolitan areas in the first pandemic wave than in the second wave, notably in recreation areas and parks. In the second wave, there was less variability in correlations over lagged time and geographic locations. Overall, we did not find conclusive evidence to support associations between lower cases and climate in all areas. Furthermore, the differences in cases-mobility correlation trends during the two pandemic waves are indicative of the effects of travel restrictions in the early phase of the pandemic and gradual return to travel routines in the later phase. This study highlights the utility of mobility data in understanding the dynamics of disease transmission. It also emphasizes the criticality of timeline and local context in interpreting transmission trends. Mobility data can capture community response to local travel restrictions at different phases of their implementation and provide insights on how these responses evolve over time alongside disease trends.

The correlation between temperature and the incidence of COVID-19 in four first-tier cities of China: a time series study

The COVID-19 outbreak emerged in Wuhan, China, and was declared a global pandemic in March 2020. This study aimed to explore the association of daily mean temperature with the daily counts of COVID-19 cases in Beijing, Shanghai, Guangzhou, and Shenzhen, China. Data on daily confirmed cases of COVID-19 and daily mean temperatures were retrieved from the 4 first-tier cities in China. Distributed lag nonlinear models (DLNMs) were used to assess the association between daily mean temperature and the daily cases of COVID-19 during the study period. After controlling for the imported risk index and long-term trends, the distributed lag nonlinear model showed that there were nonlinear and lag relationships. The daily cumulative relative risk decreased for every 1.0 °C change in temperature in Shanghai, Guangzhou, and Shenzhen. However, the cumulative relative risk increased with a daily mean temperature below - 3 °C in Beijing and then decreased. Moreover, the delayed effects of lower temperatures mostly occurred within 6-7 days of exposure. There was a negative correlation between the cumulative relative risk of COVID-19 incidence and temperature, especially when the temperature was higher than - 3 °C. The conclusions from this paper will help government and health regulators in these cities take prevention and protection measures to address the COVID-19 crisis and the possible collapse of the health system in the future.

A narrative review on the role of temperature and humidity in COVID-19: Transmission, persistence, and epidemiological evidence

Since December 2019, the 2019 coronavirus disease (COVID-19) outbreak has become a global pandemic. Understanding the role of environmental conditions is important in impeding the spread of COVID-19. Given that airborne spread and contact transmission are considered the main pathways for the spread of COVID-19, this narrative review first summarized the role of temperature and humidity in the airborne trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Meanwhile, we reviewed the persistence of the virus in aerosols and on inert surfaces and summarized how the persistence of SARS-CoV-2 is affected by temperature and humidity. We also examined the existing epidemiological evidence and addressed the limitations of these epidemiological studies. Although uncertainty remains, more evidence may support the idea that high temperature is slightly and negatively associated with COVID-19 growth, while the conclusion for humidity is still conflicting. Nonetheless, the spread of COVID-19 appears to have been controlled primarily by government interventions rather than environmental factors.

COVID-19 and Vitamin D- a Systematic Review

Introduction

The COVID-19 pandemic has strongly affected global healthcare systems. Prior epidemiological studies on different infectious diseases have shown a strong correlation between serum vitamin D levels and the incidence of certain infectious diseases. Vitamin D has an important immunomodulatory effect on innate immunity and exhibits several other mechanisms in the pathogenesis of the cytokine storm, which is one of the main contributing factors to fatality in COVID-19 patients.

Methods

A keyword search was conducted in the PubMed and Google Scholar research databases. The abstracts and/or full texts of selected papers were further evaluated. Articles that fulfilled the inclusion criteria were included in the systematic review.

Results

The 28 studies summarized in this review provide observational findings that vitamin D levels are related to the incidence, severity, and mortality rate of COVID-19 infection. The literature does not suggest that COVID-19 could be eliminated with supplementation of vitamin D, but there are implications that vitamin D deficiency might increase the risk for COVID-19 infection and severity of the disease progression.

Discussion

Current literature and several guidelines support the supplementation of vitamin D as a reasonable strategy for correcting and preventing vitamin D deficiency. The recommended dose for maintaining normal 25(OH)D levels by consensus is 1000 to 2000 IU vitamin D daily for at-risk teens and adults.

Conclusion

Vitamin D supplementation might play an important role in protecting from acute respiratory infections like the SARS CoV2, and in high-risk individuals with COVID 19 from progressing to critical clinical condition and reducing mortality.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.

Global COVID-19 Pandemic Waves: Limited Lessons Learned Worldwide over the Past Year

The occurrence of coronavirus disease 2019 (COVID-19) was followed by a small burst of cases around the world; afterward, due to a series of emergency non-pharmaceutical interventions (NPIs), the increasing number of confirmed cases slowed down in many countries. However, the lifting of control measures by the government and the public's loosening of precautionary behaviors led to a sudden increase in cases, arousing deep concern across the globe. arousing deep concern across the globe. This study evaluates the situation of the COVID-19 pandemic in countries and territories worldwide from January 2020 to February 2021. According to the time-varying reproduction number (R(t)) of each country or territory, the results show that almost half of the countries and territories in the world have never controlled the epidemic. Among the countries and territories that had once contained the occurrence, nearly half failed to maintain their prevention and control, causing the COVID-19 pandemic to rebound across the world-resulting in even higher waves in half of the rebounding countries or territories. This work also proposes and uses a time-varying country-level transmission risk score (CTRS), which takes into account both R(t) and daily new cases, to demonstrate country-level or territory-level transmission potential and trends. Time-varying hierarchical clustering of time-varying CTRS values was used to successfully reveal the countries and territories that contributed to the recent aggravation of the global pandemic in the last quarter of 2020 and the beginning of 2021, and to identify countries and territories with an increasing risk of COVID-19 transmission in the near future. Furthermore, a regression analysis indicated that the introduction and relaxation of NPIs, including workplace closure policies and stay-at-home requirements, appear to be associated with recent global transmission changes. In conclusion, a systematic evaluation of the global COVID-19 pandemic over the past year indicates that the world is now in an unexpected situation, with limited lessons learned. Summarizing the lessons learned could help in designing effective public responses for constraining future waves of COVID-19 worldwide.

How Seasonality and Control Measures Jointly Determine the Multistage Waves of the COVID-19 Epidemic: A Modelling Study and Implications

The current novel Coronavirus Disease 2019 (COVID-19) is a multistage epidemic consisting of multiple rounds of alternating outbreak and containment periods that cannot be modeled with a conventional single-stage Suspected-Exposed-Infectious-Removed (SEIR) model. Seasonality and control measures could be the two most important driving factors of the multistage epidemic. Our goal is to formulate and incorporate the influences of seasonality and control measures into an epidemic model and interpret how these two factors interact to shape the multistage epidemic curves. New confirmed cases will be collected daily from seven Northern Hemisphere countries and five Southern Hemisphere countries from March 2020 to March 2021 to fit and validate the modified model. Results show that COVID-19 is a seasonal epidemic and that epidemic curves can be clearly distinguished in the two hemispheres. Different levels of control measures between different countries during different seasonal periods have different influences on epidemic transmission. Seasonality alone cannot cause the baseline reproduction number R0 to fall below one and control measures must be taken. A superposition of a high level of seasonality and a low level of control measures can lead to a dramatically rapid increase in reported cases.

Modeling and Preliminary Analysis of the Impact of Meteorological Conditions on the COVID-19 Epidemic

Since the COVID-19 epidemic outbreak at the end of 2019, many studies regarding the impact of meteorological factors on the attack have been carried out, and inconsistent conclusions have been reached, indicating the issue's complexity. To more accurately identify the effects and patterns of meteorological factors on the epidemic, we used a combination of logistic regression (LgR) and partial least squares regression (PLSR) modeling to investigate the possible effects of common meteorological factors, including air temperature, relative humidity, wind speed, and surface pressure, on the transmission of the COVID-19 epidemic. Our analysis shows that: (1) Different countries and regions show spatial heterogeneity in the number of diagnosed patients of the epidemic, but this can be roughly classified into three types: "continuous growth", "staged shock", and "finished"; (2) Air temperature is the most significant meteorological factor influencing the transmission of the COVID-19 epidemic. Except for a few areas, regional air temperature changes and the transmission of the epidemic show a significant positive correlation, i.e., an increase in air temperature is conducive to the spread of the epidemic; (3) In different countries and regions studied, wind speed, relative humidity, and surface pressure show inconsistent correlation (and significance) with the number of diagnosed cases but show some regularity.

The influence of climate factors and government interventions on the Covid-19 pandemic: Evidence from 134 countries

This paper investigates at the world level the influence of climate on the transmission of the SARS-CoV-2 virus. For that purpose, panel regressions of the number of cases and deaths from 134 countries are run on a set of explanatory variables (air temperature, relative humidity, precipitation, and wind) along with control variables (government interventions and population size and density). The analysis is completed with a panel threshold regression to check for potential non-linearities of the weather variables on virus transmission. The main findings support the role of climate in the circulation of the virus across countries. The detailed analysis reveals that relative humidity reduces the number of cases and deaths in both low and high regimes, while temperature and wind reduce the number of deaths.

Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model

Background

Although numerous studies have explored the impact of meteorological factors on the epidemic of COVID-19, their relationship remains controversial and needs to be clarified.

Methods

We assessed the risk effect of various meteorological factors on COVID-19 infection using the distributed lag nonlinear model, based on related data from July 1, 2020, to June 30, 2021, in eight countries, including Portugal, Greece, Egypt, South Africa, Paraguay, Uruguay, South Korea, and Japan, which are in Europe, Africa, South America, and Asia, respectively. We also explored associations between COVID-19 prevalence and individual meteorological factors by the Spearman’s rank correlation test.

Results

There were significant non-linear relationships between both temperature and relative humidity and COVID-19 prevalence. In the countries located in the Northern Hemisphere with similar latitudes, the risk of COVID-19 infection was the highest at temperature below 5 ℃. In the countries located in the Southern Hemisphere with similar latitudes, their highest infection risk occurred at around 15 ℃. Nevertheless, in most countries, high temperature showed no significant association with reduced risk of COVID-19 infection. The effect pattern of relative humidity on COVID-19 depended on the range of its variation in countries. Overall, low relative humidity was correlated with increased risk of COVID-19 infection, while the high risk of infection at extremely high relative humidity could occur in some countries. In addition, relative humidity had a longer lag effect on COVID-19 than temperature.

Conclusions

The effects of meteorological factors on COVID-19 prevalence are nonlinear and hysteretic. Although low temperature and relative humidity may lower the risk of COVID-19, high temperature or relative humidity could also be associated with a high prevalence of COVID-19 in some regions.

Effectiveness of different types and levels of social distancing measures: a scoping review of global evidence from earlier stage of COVID-19 pandemic

OBJECTIVE

Social distancing is one of the main non-pharmaceutical interventions used in the control of the COVID-19 pandemic. This scoping review aims to synthesise research findings on the effectiveness of different types and levels of social distancing measures in the earlier stage of COVID-19 pandemic without the confounding effect of mass vaccination.

DESIGN

Scoping review.

DATA SOURCES

MEDLINE, Embase, Global Health and four other databases were searched for eligible studies on social distancing for COVID-19 published from inception of the databases to 30 September 2020.

STUDY SELECTION AND DATA EXTRACTION

Effectiveness studies on social distancing between individuals, school closures, workplace/business closures, public transport restrictions and partial/full lockdown were included. Non-English articles, studies in healthcare settings or not based on empirical data were excluded.

RESULTS

After screening 1638 abstracts and 8 additional articles from other sources, 41 studies were included for synthesis of findings. The review found that the outcomes of social distancing measures were mainly indicated by changes in Rt , incidence and mortality, along with indirect indicators such as daily contact frequency and travel distance. There was adequate empirical evidence for the effect of social distancing at the individual level, and for partial or full lockdown at the community level. However, at the level of social settings, the evidence was moderate for school closure, and was limited for workplace/business closures as single targeted interventions. There was no evidence for a separate effect of public transport restriction.

CONCLUSIONS

In the community setting, there was stronger evidence for the combined effect of different social distancing interventions than for a single intervention. As fatigue of preventive behaviours is an issue in public health agenda, future studies should analyse the risks in specific settings such as eateries and entertainment to implement and evaluate measures which are proportionate to the risk.

The role of climate on Covid-19 spread in France

This paper investigates the influence of climate on the transmission of the SARS-CoV-2 virus in France. Ordinary, time-varying, and threshold regressions of the number of cases and deaths are run on weather and government variables. The main findings support the role of climate in Covid-19 spread. The results reveal that a rise in temperatures is negatively associated with reported deaths, while an increase in relative humidity or wind and a decrease in precipitations are negatively associated with confirmed cases. These weather variables appear statistically significant only during the winter season.

Timing of exposure is critical in a highly sensitive model of SARS-CoV-2 transmission

Transmission efficiency is a critical factor determining the size of an outbreak of infectious disease. Indeed, the propensity of SARS-CoV-2 to transmit among humans precipitated and continues to sustain the COVID-19 pandemic. Nevertheless, the number of new cases among contacts is highly variable and underlying reasons for wide-ranging transmission outcomes remain unclear. Here, we evaluated viral spread in golden Syrian hamsters to define the impact of temporal and environmental conditions on the efficiency of SARS-CoV-2 transmission through the air. Our data show that exposure periods as brief as one hour are sufficient to support robust transmission. However, the timing after infection is critical for transmission success, with the highest frequency of transmission to contacts occurring at times of peak viral load in the donor animals. Relative humidity and temperature had no detectable impact on transmission when exposures were carried out with optimal timing and high inoculation dose. However, contrary to expectation, trends observed with sub-optimal exposure timing and lower inoculation dose suggest improved transmission at high relative humidity or high temperature. In sum, among the conditions tested, our data reveal the timing of exposure to be the strongest determinant of SARS-CoV-2 transmission success and implicate viral load as an important driver of transmission.

Novel Evidence Showing the Possible Effect of Environmental Variables on COVID-19 Spread

Coronavirus disease (COVID-19) remains a serious issue, and the role played by meteorological indicators in the process of virus spread has been a topic of academic discussion. Previous studies reached different conclusions due to inconsistent methods, disparate meteorological indicators, and specific time periods or regions. This manuscript is based on seven daily meteorological indicators in the NCEP reanalysis data set and COVID-19 data repository of Johns Hopkins University from 22 January 2020 to 1 June 2021. Results showed that worldwide average temperature and precipitable water (PW) had the strongest correlation (ρ > 0.9, p < 0.001) with the confirmed COVID-19 cases per day from 22 January to 31 August 2020. From 22 January to 31 August 2020, positive correlations were observed between the temperature/PW and confirmed COVID-19 cases/deaths in the northern hemisphere, whereas negative correlations were recorded in the southern hemisphere. From 1 September to 31 December 2020, the opposite results were observed. Correlations were weak throughout the near full year, and weak negative correlations were detected worldwide (|ρ| < 0.4, p ≤ 0.05); the lag time had no obvious effect. As the latitude increased, the temperature and PW of the maximum confirmed COVID-19 cases/deaths per day generally showed a decreasing trend; the 2020-year fitting functions of the response latitude pattern were verified by the 2021 data. Meteorological indicators, although not a decisive factor, may influence the virus spread by affecting the virus survival rates and enthusiasm of human activities. The temperature or PW threshold suitable for the spread of COVID-19 may increase as the latitude decreases.

Economic burden of public health care and hospitalisation associated with COVID-19 in China

OBJECTIVES

This study aimed to evaluate the socio-economic burden imposed on the Chinese healthcare system during the coronavirus disease 2019 (COVID-19) pandemic.

STUDY DESIGN

A cross-sectional study was used to investigate how COVID-19 impacted health and medical costs in China. Data were derived from a subdivision of the Centers for Disease control and Prevention of China.

METHODS

We prospectively collected information from the Centers for Disease Control and Prevention and the designated hospitals to determine the cost of public health care and hospitalisation due to COVID-19. We estimated the resource use and direct medical costs associated with public health.

RESULTS

The average costs, per case, for specimen collection and nucleic acid testing (NAT [specifically, polymerase chain reaction {PCR}]) in low-risk populations were $29.49 and $53.44, respectively; however, the average cost of NAT in high-risk populations was $297.94 per capita. The average costs per 1000 population for epidemiological surveys, disinfectant, health education and centralised isolation were $49.54, $247.01, $90.22 and $543.72, respectively. A single hospitalisation for COVID-19 in China cost a median of $2158.06 ($1961.13-$2325.65) in direct medical costs incurred only during hospitalisation, whereas the total costs associated with hospitalisation of patients with COVID-19 were estimated to have reached nearly $373.20 million in China as of 20, May, 2020. The cost of public health care associated with COVID-19 as of 20, May, 2020 ($6.83 billion) was 18.31 times that of hospitalisation.

CONCLUSIONS

This study highlights the magnitude of resources needed to treat patients with COVID-19 and control the COVID-19 pandemic. Public health measures implemented by the Chinese government have been valuable in reducing the infection rate and may be cost-effective ways to control emerging infectious diseases.

Downstream health impacts of employment losses during the COVID-19 pandemic

OBJECTIVES

The Canadian workforce has experienced significant employment losses during the COVID-19 pandemic, in part as a result of non-pharmaceutical interventions to slow COVID-19 transmission. Health consequences are likely to result from these job losses, but without historical precedent for the current economic shutdown they are challenging to plan for. Our study aimed to use population risk models to quantify potential downstream health impacts of the COVID-19 pandemic and inform public health planning to minimize future health burden.

METHODS

The impact of COVID-19 job losses on future premature mortality and high-resource health care utilization (HRU) was estimated using an economic model of Canadian COVID-19 lockdowns and validated population risk models. Five-year excess premature mortality and HRU were estimated by age and sex to describe employment-related health consequences of COVID-19 lockdowns in the Canadian population.

RESULTS

With federal income supplementation like the Canadian Emergency Response Benefit, we estimate that each month of economic lockdown will result in 5.6 new high-resource health care system users (HRUs), and 4.1 excess premature deaths, per 100,000, over the next 5 years. These effects were concentrated in ages 45-64, and among males 18-34. Without income supplementation, the health consequences were approximately twice as great in terms of both HRUs and premature deaths.

CONCLUSION

Employment losses associated with COVID-19 countermeasures may have downstream implications for health. Public health responses should consider financially vulnerable populations at high risk of downstream health outcomes.

School and community reopening during the COVID-19 pandemic: a mathematical modelling study

Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

Impact of school closures and re-openings on COVID-19 transmission

BACKGROUND

Globally, the education of students at primary and secondary schools has been severely disrupted by the implementation of school closures to reduce the spread of coronavirus disease 2019 (COVID-19). The effectiveness of school closures in reducing transmission of COVID-19 and the impact of re-opening schools are unclear.

METHODS

Research criteria for this rapid review included empirical studies, published or pre-published worldwide before January 25, 2021, that assessed the effectiveness of school closures in reducing the spread of COVID-19 and the impact of school re-openings on COVID-19 transmission.

RESULTS

Twenty-four studies on the impact of school closures and re-openings on COVID-19 transmission were identified through the seven databases that were searched. Overall the evidence from these studies was mixed and varied due to several factors such as the time of implementation of public health measures, research design of included studies and variability among the levels of schooling examined.

CONCLUSION

Preliminary findings suggest that school closures have limited impact on reducing COVID-19 transmission, with other non-pharmaceutical interventions considered much more effective. However, due to the limitations of the studies, further research is needed to support the use of this public health measure in response to the COVID-19 pandemic.

The Effects of Climate and Bioclimate on COVID-19 Cases in Poland

The correlations between air temperatures, relative and absolute humidity, wind, cloudiness, precipitation and number of influenza cases have been extensively studied in the past. Because, initially, COVID-19 cases were similar to influenza cases, researchers were prompted to look for similar relationships. The aim of the study is to identify the effects of changes in air temperature on the number of COVID-19 infections in Poland. The hypothesis under consideration concerns an increase in the number of COVID-19 cases as temperature decreases. The spatial heterogeneity of the relationship under study during the first year and a half of the COVID-19 pandemic in Polish counties is thus revealed.

Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2

As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2-the receptor of SARS-CoV-2 in human cells-and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8-3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19.

COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games

The 2020 Olympic/Paralympic Games have been postponed to 2021, due to the COVID-19 pandemic. We developed a model that integrated source-environment-receptor pathways to evaluate how preventive efforts can reduce the infection risk among spectators at the opening ceremony of Tokyo Olympic Games. We simulated viral loads of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emitted from infectors through talking/coughing/sneezing and modeled temporal environmental behaviors, including virus inactivation and transfer. We performed Monte Carlo simulations to estimate the expected number of newly infected individuals with and without preventive measures, yielding the crude probability of a spectator being an infector among the 60,000 people expected to attend the opening ceremony. Two indicators, i.e., the expected number of newly infected individuals and the newly infected individuals per infector entry, were proposed to demonstrate the extent of achievable infection risk reduction levels by implementing possible preventive measures. A no-prevention scenario produced 1.5-1.7 newly infected individuals per infector entry, whereas a combination of cooperative preventive measures by organizers and the spectators achieved a 99% risk reduction, corresponding to 0.009-0.012 newly infected individuals per infector entry. The expected number of newly infected individuals was calculated as 0.005 for the combination of cooperative preventive scenarios with the crude probability of a spectator being an infector of 1 × 10^-5. Based on our estimates, a combination of cooperative preventions between organizers and spectators is required to prevent a viral spread at the Tokyo Olympic/Paralympic Games. Further, under the assumption that society accepts < 10 newly infected persons traced to events held during the entire Olympic/Paralympic Games, we propose a crude probability of infectors of < 5 × 10^-5 as a benchmark for the suppression of the infection. This is the first study to develop a model that can assess the infection risk among spectators due to exposure pathways at a mass gathering event.

A multiplicity of environmental, economic and social factor analyses to understand COVID-19 diffusion

Research on the impact of the environment on COVID-19 diffusion lacks a full-comprehensive perspective, and neglecting the multiplicity of the human-environment system can lead to misleading conclusions. We attempted to reveal all pre-existing environmental-to-human and human-to-human determinants that influence the transmission of COVID-19. As such, We estimated the daily case incidence ratios (CIR) of COVID-19 for prefectures across mainland China, and used a mixed-effects mixed-distribution model to study the association between the CIR and 114 factors related to climate, atmospheric environmental quality, terrain, population, economic, human mobility as well as non-pharmaceutical interventions (NPIs). Not only the changes in determinants over time as the pandemic progresses but also their lag and interaction effects were examined. CO, O3, PM10 and PM2.5 were found positively linked with CIR, but the effect of NO2 was negative. The temperature had no significant association with CIR, and the daily minimum humidity was a significant negatively predictor. NPIs' level was negatively associated with CIR until with a lag of 15 days. Higher accumulated destination migration scale flow from the epicenter and lower distance to the epicenter (DisWH) were associated with a higher CIR, however, the interaction between DisWH and the time was positive. The more economically developed and more densely populated cities have a higher probability of CIR occurrence, but they may not have a higher CIR intensity.The COVID-19 diffusion are caused by a multiplicity of environmental, economic, social factors as well as NPIs. First, multiple pollutants carried simultaneously on particulate matter affect COVID-19 transmission. Second, the temperature has a limited impact on the spread of the epidemic. Third, NPIs must last for at least 15 days or longer before the effect has been apparent. Fourth, the impact of population movement from the epicenter on COVID-19 gradually diminished over time and intraregional migration deserves more attention.

Disability and self-care living strategies among adults living with HIV during the COVID-19 pandemic

BACKGROUND

Events associated with the COVID-19 pandemic, such as physical distancing, closure of community services, postponement of health appointments, and loss of employment can lead to social isolation, financial uncertainty, and interruption of antiretroviral adherence, resulting in additional health-related challenges (disability) experienced among adults living with chronic illness such as HIV. 'Living strategies' is a concept derived from the perspectives of people living with HIV, defined as behaviors, attitudes and beliefs adopted by people living with HIV to help deal with disability associated with HIV and multi-morbidity. Our aim was to describe disability among adults living with HIV and self-care living strategies used during the COVID-19 pandemic.

METHODS

Adults living with HIV in Toronto, Ontario, Canada, including some with pre-pandemic HIV Disability Questionnaire (HDQ) data, completed a cross-sectional web-based survey between June-August 2020. The survey included the HDQ and questions about self-care living strategy use during the pandemic. We compared disability (HDQ) scores prior to versus during the pandemic using paired t-tests. We reported the proportion of participants who engaged in various living strategies at least 'a few times a week' or 'everyday' during the pandemic.

RESULTS

Of the 63 respondents, 84% were men, median age 57 years, and 62% lived alone. During the pandemic the greatest disability severity was in the uncertainty [median 30; Interquartile range (IQR): 16, 43] and mental-emotional (25; IQR: 14, 41) domains. Among the 51 participants with pre-pandemic data, HDQ severity scores were significantly greater (worse) during the pandemic (vs prior) in all domains. Greatest change from prior to during the pandemic was in the mental-emotional domain for presence (17.7; p < 0.001), severity (11.4; p < 0.001), and episodic nature (9.3; p < 0.05) of disability. Most participants (> 60%) reported engaging a 'few times a week' or 'everyday' in self-care strategies associated with maintaining sense of control and adopting positive attitudes and beliefs.

CONCLUSIONS

People living with HIV reported high levels of uncertainty and mental-emotional health challenges during the pandemic. Disability increased across all HDQ dimensions, with the greatest worsening in the mental-emotional health domain. Results provide an understanding of disability and self-care strategy use during the COVID-19 pandemic.

Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis

OBJECTIVE

To review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Medline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints).

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Observational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.

MAIN OUTCOME MEASURES

The main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality.

DATA SYNTHESIS

DerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values.

RESULTS

72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a "package of interventions." Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively.

CONCLUSIONS

This systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020178692.

A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries

There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission.

Physical distancing implementation, ambient temperature and Covid-19 containment: An observational study in the United States

Governments may relax physical distancing interventions for coronavirus disease 2019 (Covid-19) containment in warm seasons/areas to prevent economic contractions. However, it is not clear whether higher temperature may offset the transmission risk posed by this relaxation. This study aims to investigate the associations of the effective reproductive number (R_t) of Covid-19 with ambient temperature and the implementation of physical distancing interventions in the United States (US). This study included 50 states and one territory of the US with 4,532,650 confirmed cases between 29 January and 31 July 2020. We used an interrupted time-series model with a state-level random intercept for data analysis. An interaction term of 'physical distancing×temperature' was included to examine their interactions. Stratified analyses by temperature and physical distancing implementation were also performed to analyse the modifying effects. The overall median (interquartile range) R_t was 1.2 (1.0-2.3). The implementation of physical distancing was associated with a 12% decrease in the risk of R_t (relative risk [RR]: 0.88, 95% confident interval [CI]: 0.86-0.89), and each 5 °C increase in temperature was associated with a 2% decrease (RR: 0.98, 95%CI: 0.97-0.98). We observed a statistically significant interaction between temperature and physical distancing implementation, but all the RRs were small (close to one). The containing effects of high temperature were attenuated by 5.1% when physical distancing was implemented. The association of COVID-19 R_t with physical distancing implementation was more stable (0.88 vs. 0.89 in days when temperature was low and high, respectively). Increased temperature did not offset the risk of Covid-19 R_t posed by the relaxation of physical distancing implementation. Our study does not recommend relaxing the implementation of physical distancing interventions in warm seasons/areas.

COVID-19's U.S. Temperature Response Profile

We estimate the U.S. temperature response profile (TRP) for COVID-19 and show it is highly sensitive to temperature variation. Replacing the erratic daily death counts U.S. states initially reported with counts based on death certificate date, we build a week-ahead statistical forecasting model that explains most of their daily variation (R2 = 0.97) and isolates COVID-19's TRP (p < 0.001). These counts, normalized at 31 °C (U.S. mid-summer average), scale up to 160% at 5 °C in the static case where the infection pool is held constant. Positive case counts are substantially more temperature sensitive. When temperatures are declining, dynamic feedback through a growing infection pool can substantially amplify these temperature effects. Our estimated TRP can be incorporated into COVID-related planning exercises and used as an input to SEIR models employed for longer run forecasting. For the former, we show how our TRP is predictive of the realized pattern of growth rates in per capita positive cases across states five months after the end of our sample period. For the latter, we show the variation in herd immunity levels implied by temperature-driven, time-varying R0 series for the Alpha and Delta variants of COVID-19 for several representative states.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10640-021-00603-8.

COVID-19-associated school closures and related efforts to sustain education and subsidized meal programs, United States, February 18-June 30, 2020

Pre-emptive school closures are frontline community mitigation measures recommended by the US Centers for Disease Control and Prevention (CDC) for implementation during severe pandemics. This study describes the spatiotemporal patterns of publicly announced school closures implemented in response to the coronavirus disease 2019 (COVID-19) pandemic and assesses how public K-12 districts adjusted their methods of education delivery and provision of subsidized meals. During February 18–June 30, 2020, we used daily systematic media searches to identify publicly announced COVID-19–related school closures lasting ≥1 day in the United States (US). We also collected statewide school closure policies from state government websites. Data on distance learning and subsidized meal programs were collected from a stratified sample of 600 school districts. The first COVID-19–associated school closure occurred on February 27, 2020 in Washington state. By March 30, 2020, all but one US public school districts were closed, representing the first-ever nearly synchronous nationwide closure of public K-12 schools in the US. Approximately 100,000 public schools were closed for ≥8 weeks because of COVID-19, affecting >50 million K-12 students. Of 600 districts sampled, the vast majority offered distance learning (91.0%) and continued provision of subsidized meal programs (78.8%) during the closures. Despite the sudden and prolonged nature of COVID-19–associated school closures, schools demonstrated flexibility by implementing distance learning and alternate methods to continue subsidized meal programs.