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Background: This study aimed to assess the impact of the COVID-19 pandemic on the disease burden of Taiwan's notifiable infectious diseases (NIDs). We compared disease burdens between the pandemic and pre-pandemic year of 2020 (with non-pharmaceutical interventions (NPIs)) and 2010 (without NPIs), respectively, to understand the overall pandemic impact on NIDs in Taiwan. Methods: Forty-three national NIDs were analyzed using the Statistics of Communicable Diseases and Surveillance Report by estimating the premature death and disability via different transmission categories, sex, and age groups. The study evaluated the impact of diseases by assessing the years lost due to death (YLLs), the duration of living with disability (YLDs), and the overall disability-adjusted life years (DALYs) by measuring both the severity of the illness and its duration. Results: Taiwan recorded 1,577 (2010) and 1,260 (2020) DALYs per million population and lost 43 NIDs, decreasing 317 DALYs per million population. Tuberculosis, HIV/AIDS and acute hepatitis B/D were the leading causes of DALYs, accounting for 89% (2010) and 77% (2020). Conclusion: Overall, this study provided the first insight of changes in disease burdens in NIDs between pre- and post-COVID-19 based on a nationwide viewpoint for further preventive measures and interventions to be focused on specific diseases by associated health administrations and policies. [ABSTRACT FROM AUTHOR]

Background: Understanding how the COVID-19 pandemic evolved under control measures is crucial to tackle the SARS-CoV-2 virus spread. Laos, a country bordering China but with late occurrence and low burden of COVID-19 compared to its neighbouring countries, was used for a case study. Methods: A transmission model with disease reporting was proposed to investigate the impact of control measures on the SARS-CoV-2 virus spread in Laos from April 2021 to May 2022. It was assumed that the transmission rate changed with people's behaviours, control measures and emerging variants; susceptibility decreased with vaccination and infection. Bayesian inference was used for model calibration to data of confirmed cases, deaths, and recoveries, and the deviance information criterion was used to select the best model variant. Results: Our model including Non-pharmaceutical interventions (NPIs), behaviour change, vaccination, and changing variants well explained the three waves in Laos. The Alpha variant was estimated to have a basic reproduction number of 1.55 (95% CrI: 1.47–1.64) and was replaced by the Delta variant from September 2021 which was 1.88 (95% CrI: 1.77–2.01) times more transmissible; the Delta variant was replaced by Omicron variant from March 2022 which was 3.33 (95% CrI: 2.84–3.74) times more transmissible. The Delta variant was the most severe with a case fatality rate of 1.05% (95% CrI: 0.96–1.15%) while the Alpha variant and Omicron variant were much milder. The ascertainment rate was low and variable: first decreasing from 13.2 to 1.8% by 23 May 2021, and then increasing to 23.4% by 15 March 2022. Counterfactual simulations indicated that vaccination played strong roles in reducing infections even under the emergence of immune escape variants while behaviour change delayed but might not flatten the peak of outbreaks. Conclusions: The three waves of Laos' epidemics were due to the invasion of more transmissible and immune escape variants that affected the herd immunity built via vaccination and infection. Even with immunity waning and the escape of new variants, vaccination was still the major contributor to control COVID-19 and combining behaviour changes and vaccination would best suppress future outbreaks of COVID-19. [ABSTRACT FROM AUTHOR]

COVID-19 has affected the various aspects of social service delivery worldwide. Explicitly, pediatric service was affected mainly due to the travel restrictions, and children were at heightened risk due to these circumstances. Therefore, this study aims to analyze the Pediatric Clinical Practice in a Chinese children's hospital to describe and acknowledge the impact of COVID-19 on the pediatric healthcare system. For this purpose, the hospital's outpatient registration database was the primary information source, which comprises demographic data, including age, gender, city of residence, and hospital departments visited. Data on patients admitted from January 25, 2019, to April 16, 2019, were collected and used as a baseline. The results revealed that the number of pediatric visits to the case study hospital decreased during the COVID-19 pandemic, accounting for 40% of that in 2019, especially during the early stage of the pandemic. The proportion of pediatric patients from outside Chongqing decreased by approximately 14% in the early stages and increased by 24% in the second and third stages, corresponding to an overall decrease of 8.5%. Accordingly, the hospital responds to COVID-19 by providing valuable information and a guiding framework to the rest of the world on how to respond to a crisis. [ABSTRACT FROM AUTHOR]

The purpose is to examine the impact of the perceived effectiveness of NPIs (e.g., hand hygiene, respiratory etiquette, face masks) on behavioral intentions, attitudes toward usage, and actual use against the backdrop of the Technology Acceptance Model (TAM). Responses were gathered with a survey instrument from Canadian respondents (N= 278). PLS-SEM and exploratory factor analysis (EFA) were used as analytical methods. The hypotheses between the key constructs were accepted consistently with TAM. Also, the results show a positive relationship between perceived effectiveness and attitude toward the usage of NPIs. However, the perceived effectiveness did not significantly impact behavioral intentions and actual use of NPIs. A significant indirect relationship was discovered between perceived effectiveness via attitudes on behavioral intentions and the actual use of NPIs. The perceptions of the respondents who perceived the NPIs to be effective and those who did not were quite similar. The current research provides a framework for effectively promoting the relevant behaviors while utilizing the Technology Acceptance Model (TAM) framework. The critical role of attitude toward the use of NPIs is highlighted through the direct impact of perceived effectiveness and the indirect effect of perceived effectiveness on behavioral intentions and actual usage toward the use of NPIs. [ABSTRACT FROM AUTHOR]

Background This study aimed to assess the impact of the COVID-19 pandemic on the disease burden of Taiwan’s notifiable infectious diseases (NIDs). We compared disease burdens between the pandemic and pre-pandemic year of 2020 (with non-pharmaceutical interventions (NPIs)) and 2010 (without NPIs), respectively, to understand the overall pandemic impact on NIDs in Taiwan. Methods Forty-three national NIDs were analyzed using the Statistics of Communicable Diseases and Surveillance Report by estimating the premature death and disability via different transmission categories, sex, and age groups. The study evaluated the impact of diseases by assessing the years lost due to death (YLLs), the duration of living with disability (YLDs), and the overall disability-adjusted life years (DALYs) by measuring both the severity of the illness and its duration. Results Taiwan recorded 1,577 (2010) and 1,260 (2020) DALYs per million population and lost 43 NIDs, decreasing 317 DALYs per million population. Tuberculosis, HIV/AIDS and acute hepatitis B/D were the leading causes of DALYs, accounting for 89% (2010) and 77% (2020). Conclusion Overall, this study provided the first insight of changes in disease burdens in NIDs between pre- and post-COVID-19 based on a nationwide viewpoint for further preventive measures and interventions to be focused on specific diseases by associated health administrations and policies.

Threatening tourism's core values, COVID-19 forced a global lockdown with unprecedent economic ramifications across the industry's sectors. By espousing an econometric methodology, this study investigates the pandemic's impact on hospitality and tourism (H/T) stock indices trading in five European stock markets and explores the effect of both state-enforced, non-pharmaceutical interventions (NPIs) and vaccinations. Findings suggest that a) the pandemic was the most impactful event in history to affect H/T stock indices trading in major European financial markets; b) the tourism industry reacted differently to the pandemic compared to other major economic sectors; and c) government-enforced measures directly targeting the industry's core operations had a powerful effect on both stock returns and volatility during the first year of the pandemic, nevertheless, for returns, this effect was mitigated by the rollout of vaccinations. The study enriches our collective knowledge on the impact of COVID-19 on the economics of tourism, with emphasis on H/T stock indices. [ABSTRACT FROM AUTHOR]

Previous studies that extended the Theory of Planned Behaviour (TPB) with the Health Belief Model (HBM) did not integrate all constructs. To address this research gap, we combined those two theories and the subscale on Domain-Specific Risk-Taking (DOSPERT) to predict tourists' willingness to apply NPIs against COVID-19 while travelling. The proposed hypotheses on the mediating role of attitudes were tested using structural equation modelling based on a random sampling of the Swiss population (n = 1683). The results indicate that attitudes are the strongest predictor of behavioural intentions to apply NPIs while travelling. Attitude also acts as a mediator between health beliefs and the willingness to apply protective measures voluntary for the next tourism trip. The results permit some managerial implications to be suggested for supporting preventive travel behaviour. [ABSTRACT FROM AUTHOR]

The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo. [ABSTRACT FROM AUTHOR]

Abstract 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

Purpose: Against the backdrop of the technology acceptance model (TAM), theory of reasoned action, and social impact theory the purpose of this research is to examine the validity of the TAM and assess the impact of social influence on the usage of NPIs in order to determine how best to encourage people to engage in the use of NPIs. Design/methodology/approach: A survey instrument was used to gather data with a snowball sampling method from Canadian respondents. The survey questionnaire items were adapted from existing literature. Data analysis was done using PLS-SEM. Findings: The results indicate that the TAM framework is applicable in the context of the use of NPIs with the COVID-19 outbreak as all TAM relationships were positive and significant. In addition, the results show a positive and significant impact of social influence on perceived usefulness, attitudes, and behavioral intentions towards the usage of NPIs. Thus, social forces can be considered relevant when understanding the adoption of technology. Originality/value: This research gives a better understanding of how social influence impacts adoption of behavior, such as the use of NPIs, and can be used to support the use of NPIs to decrease the spreading of viruses. [ABSTRACT FROM AUTHOR]

BackgroundThe 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.MethodsThis 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.ResultsThe 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.ConclusionOur 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.

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. [ABSTRACT FROM AUTHOR]

Coronavirus Disease (COVID-19), which began as a small outbreak in Wuhan, China, in December 2019, became a global pandemic within months due to its high transmissibility. In the absence of pharmaceutical treatment, various non-pharmaceutical interventions (NPIs) to contain the spread of COVID-19 brought the entire world to a halt. After almost a year of seemingly returning to normalcy with the world's quickest vaccine development, the emergence of more infectious and vaccine resistant coronavirus variants is bringing the situation back to where it was a year ago. In the light of this new situation, we conducted a study to portray the possible scenarios based on the three key factors: impact of interventions (pharmaceutical and NPIs), vaccination rate, and vaccine efficacy. In our study, we assessed two of the most crucial factors, transmissibility and vaccination rate, in order to reduce the spreading of COVID-19 in a simple but effective manner. In order to incorporate the time-varying mutational landscape of COVID-19 variants, we estimated a weighted transmissibility composed of the proportion of existing strains that naturally vary over time. Additionally, we consider time varying vaccination rates based on the number of daily new cases. Our method for calculating the vaccination rate from past active cases is an effective approach in forecasting probable future scenarios as it actively tracks people's attitudes toward immunization as active case changes. Our simulations show that if a large number of individuals cannot be vaccinated by ensuring high efficacy in a short period of time, adopting NPIs is the best approach to manage disease transmission with the emergence of new vaccine breakthrough and more infectious variants.

The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo.

Abstract Background Bronchiolitis is the most common viral infection of the lower respiratory tract in infants under 2 years of age. The aim of this study was to analyze and compare the seasonal bronchiolitis peaks before and during the SARS-CoV-2 pandemic. Methods Descriptive, prospective, and observational study. Patients with severe bronchiolitis admitted to the Pediatric Intensive Care Unit (PICU) of a referral tertiary hospital between September 2010 and June 2021 were included. Demographic data were collected. Viral laboratory-confirmation was carried out. Each season was analyzed and compared. The daily average temperature was collected. Results 1116 patients were recruited, 58.2% of them males. The median age was 49 days. Respiratory syncytial virus (RSV) was isolated in 782 cases (70.1%). In April 2021, the first and only case of bronchiolitis caused by SARS-CoV-2 was identified. The pre- and post-pandemic periods were compared. There were statistically significant differences regarding: age, 47 vs. 73 days (p = 0.006), PICU and hospital length of stay (p = 0.024 and p = 0.001, respectively), and etiology (p = 0.031). The peak for bronchiolitis in 2020 was non-existent before week 52. A delayed peak was seen around week 26/2021. The mean temperature during the epidemic peak was 10ºC for the years of the last decade and is 23ºC for the present season. Conclusion The COVID-19 pandemic outbreak has led to a clearly observable epidemiological change regarding acute bronchiolitis, which should be studied in detail. The influence of the environmental temperature does not seem to determine the viral circulation.

The Korean government’s public health responses to the COVID-19 epidemic have achieved a remarkable outcome in terms of the measured number of infected patients and the overall mortality rate. Nonetheless, the public health authority’s various mitigation strategies and vaccination efforts have faced several challenges primarily posed by politically motivated Christian fundamentalists and ultraconservative media’s distorted news framing in Korea. This paper examines how these conservative forces – both religious and political – have undermined the Korean public health authority’s various mitigation efforts and discusses how to address the problems from a public policy point of view. The paper argues that a comprehensive legal reform including the introduction of effective punitive damages in the media market is a necessary minimum to address some of these problems.

Summary: 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.

BackgroundNew variants of SARS-CoV-2 are constantly discovered. Administration of COVID-19 vaccines and booster doses, combined with the application of non-pharmaceutical interventions (NPIs), is often used to prevent outbreaks of emerging variants. Such outbreak dynamics are further complicated by the population's behavior and demographic composition. Hence, realistic simulations are needed to estimate the efficiency of proposed vaccination strategies in conjunction with NPIs.MethodsWe developed an individual-based model of COVID-19 dynamics that considers age-dependent parameters such as contact matrices, probabilities of symptomatic and severe disease, and households' age distribution. As a case study, we simulate outbreak dynamics under the demographic compositions of two Israeli cities with different household sizes and age distributions. We compare two vaccination strategies: vaccinate individuals in a currently prioritized age group, or dynamically prioritize neighborhoods with a high estimated reproductive number. Total infections and hospitalizations are used to compare the efficiency of the vaccination strategies under the two demographic structures, in conjunction with different NPIs.ResultsWe demonstrate the effectiveness of vaccination strategies targeting highly infected localities and of NPIs actively detecting asymptomatic infections. We further show that different optimal vaccination strategies exist for each sub-population's demographic composition and that their application is superior to a uniformly applied strategy.ConclusionOur study emphasizes the importance of tailoring vaccination strategies to subpopulations' infection rates and to the unique characteristics of their demographics (e.g., household size and age distributions). The presented simulation framework and findings can help better design future responses against the following emerging variants.

Background: Non-pharmaceutical interventions (NPIs) used to limit SARS-CoV-2 transmission vary in their feasibility, appropriateness and effectiveness in different contexts. In Bangladesh a national lockdown implemented in March 2020 exacerbated poverty and was untenable long-term. A resurgence in 2021 warranted renewed NPIs. We sought to identify NPIs that were feasible in this context and explore potential synergies between interventions. Methods: We developed an SEIR model for Dhaka District, parameterised from literature values and calibrated to data from Bangladesh. We discussed scenarios and parameterisations with policymakers with the aid of an interactive app. These discussions guided modelling of lockdown and two post-lockdown measures considered feasible to deliver; symptoms-based household quarantining and compulsory mask-wearing. We compared NPI scenarios on deaths, hospitalisations relative to capacity, working days lost, and cost-effectiveness. Results: Lockdowns alone were predicted to delay the first epidemic peak but could not prevent overwhelming of the health service and were costly in lost working days. Impacts of post-lockdown interventions depended heavily on compliance. Assuming 80% compliance, symptoms-based household quarantining alone could not prevent hospitalisations exceeding capacity, whilst mask-wearing prevented overwhelming health services and was cost-effective given masks of high filtration efficiency. Combining masks with quarantine increased their impact. Recalibration to surging cases in 2021 suggested potential for a further wave in 2021, dependent on uncertainties in case reporting and immunity. Conclusions: Masks and symptoms-based household quarantining synergistically prevent transmission, and are cost-effective in Bangladesh. Our interactive app was valuable in supporting decision-making, with mask-wearing being mandated early, and community teams being deployed to support quarantining across Dhaka. These measures likely contributed to averting the worst public health impacts, but delivering an effective response with consistent compliance across the population has been challenging. In the event of a further resurgence, concurrent messaging to increase compliance with both mask-wearing and quarantine is recommended.

Coronavirus Disease (COVID-19), which began as a small outbreak in Wuhan, China, in December 2019, became a global pandemic within months due to its high transmissibility. In the absence of pharmaceutical treatment, various non-pharmaceutical interventions (NPIs) to contain the spread of COVID-19 brought the entire world to a halt. After almost a year of seemingly returning to normalcy with the world's quickest vaccine development, the emergence of more infectious and vaccine resistant coronavirus variants is bringing the situation back to where it was a year ago. In the light of this new situation, we conducted a study to portray the possible scenarios based on the three key factors: impact of interventions (pharmaceutical and NPIs), vaccination rate, and vaccine efficacy. In our study, we assessed two of the most crucial factors, transmissibility and vaccination rate, in order to reduce the spreading of COVID-19 in a simple but effective manner. In order to incorporate the time-varying mutational landscape of COVID-19 variants, we estimated a weighted transmissibility composed of the proportion of existing strains that naturally vary over time. Additionally, we consider time varying vaccination rates based on the number of daily new cases. Our method for calculating the vaccination rate from past active cases is an effective approach in forecasting probable future scenarios as it actively tracks people's attitudes toward immunization as active case changes. Our simulations show that if a large number of individuals cannot be vaccinated by ensuring high efficacy in a short period of time, adopting NPIs is the best approach to manage disease transmission with the emergence of new vaccine breakthrough and more infectious variants. [ABSTRACT FROM AUTHOR]

India has been the latest global epicenter for COVID-19, a novel coronavirus disease that emerged in China in late 2019. We present a base mathematical model for the transmission dynamics of COVID-19 in India and its neighbor, Pakistan. The base model was rigorously analyzed and parameterized using cumulative COVID-19 mortality data from each of the two countries. The model was used to assess the population-level impact of the control and mitigation strategies implemented in the two countries (notably non-pharmaceutical interventions). Numerical simulations of the basic model indicate that, based on the current baseline levels of the control and mitigation strategies implemented, the pandemic trajectory in India is on a downward trend. This downward trend will be reversed, and India will be recording mild outbreaks, if the control and mitigation strategies are relaxed from their current levels. By early September 2021, our simulations suggest that India could record up to 460,000 cumulative deaths under baseline levels of the implemented control strategies, while Pakistan (where the pandemic is comparatively milder) could see over 24,000 cumulative deaths at current mitigation levels. The basic model was extended to assess the impact of back-and-forth mobility between the two countries. Simulations of the resulting metapopulation model show that the burden of the COVID-19 pandemic in Pakistan increases with increasing values of the average time residents of India spend in Pakistan, with daily mortality in Pakistan peaking in mid-August to mid-September of 2021. Under the respective baseline control scenarios, our simulations show that the back-and-forth mobility between India and Pakistan could delay the time-to-elimination of the COVID-19 pandemic in India and Pakistan to November 2022 and July 2022, respectively.

AbstractBackground This paper uses a SEIR(D) model to analyse the time-varying transmission dynamics of the COVID-19 epidemic in Korea throughout its multiple stages of development. This multi-stage estimation of the model parameters offers a better model fit compared to the whole period analysis and shows how the COVID-19’s infection patterns change over time, primarily depending on the effectiveness of the public health authority’s non-pharmaceutical interventions (NPIs).Methods This paper uses the SEIR(D) compartment model to simulate and estimate the parameters for three distinctive stages of the COVID-19 epidemic in Korea, using a manually compiled COVID-19 epidemic dataset for the period between 18 February 2020 and 08 February 2021. The paper identifies three major stages of the COVID-19 epidemic, conducts multi-stage estimations of the SEIR(D) model parameters, and carefully infers context-dependent meaning of the estimation results to help better understand the unique patterns of the transmission of the novel coronavirus (SARS-CoV-2) in each stage.Results The original SIR compartment model may produce a poor and even misleading estimation result if it is used to cover the entire period of the epidemic. However, if we use the model carefully in distinctive stages of the COVID-19 epidemic, we can find useful insights into the nature of the transmission of the novel coronavirus and the relative effectiveness of the government’s non-pharmaceutical interventions over time.Key messagesIdentifies three distinctive waves of the COVID-19 epidemic in Korea.Conducts multi-stage estimations of the COVID-19 transmission dynamics using SEIR(D) epidemic models.The transmission dynamics of the COVID-19 vary over time, primarily depending on the relative effectiveness of the government’s non-pharmaceutical interventions (NPIs).The SEIR(D) epidemic model is useful and informative, but only when it is used carefully to account for the presence of multiple waves and context-dependent infection patterns in each wave.

Background: Bronchiolitis is the most common viral infection of the lower respiratory tract in infants under 2 years of age. The aim of this study was to analyze and compare the seasonal bronchiolitis peaks before and during the SARS-CoV-2 pandemic.Methods: Descriptive, prospective, and observational study. Patients with severe bronchiolitis admitted to the Pediatric Intensive Care Unit (PICU) of a referral tertiary hospital between September 2010 and June 2021 were included. Demographic data were collected. Viral laboratory-confirmation was carried out. Each season was analyzed and compared. The daily average temperature was collected.Results: 1116 patients were recruited, 58.2% of them males. The median age was 49 days. Respiratory syncytial virus (RSV) was isolated in 782 cases (70.1%). In April 2021, the first and only case of bronchiolitis caused by SARS-CoV-2 was identified. The pre- and post-pandemic periods were compared. There were statistically significant differences regarding: age, 47 vs. 73 days (p = 0.006), PICU and hospital length of stay (p = 0.024 and p = 0.001, respectively), and etiology (p = 0.031). The peak for bronchiolitis in 2020 was non-existent before week 52. A delayed peak was seen around week 26/2021. The mean temperature during the epidemic peak was 10ºC for the years of the last decade and is 23ºC for the present season.Conclusion: The COVID-19 pandemic outbreak has led to a clearly observable epidemiological change regarding acute bronchiolitis, which should be studied in detail. The influence of the environmental temperature does not seem to determine the viral circulation. [ABSTRACT FROM AUTHOR]

A mathematical model is designed and used to study the transmission dynamics and control of COVID-19 in Nigeria. The model, which was rigorously analysed and parametrized using COVID-19 data published by the Nigeria Centre for Disease Control (NCDC), was used to assess the community-wide impact of various control and mitigation strategies in some jurisdictions within Nigeria (notably the states of Kano and Lagos, and the Federal Capital Territory, Abuja). Numerical simulations of the model showed that COVID-19 can be effectively controlled in Nigeria using moderate levels of social-distancing strategy in the jurisdictions and in the entire nation. Although the use of face masks in public can significantly reduce COVID-19 in Nigeria, its use, as a sole intervention strategy, may fail to lead to a substantial reduction in disease burden. Such substantial reduction is feasible in the jurisdictions (and the entire Nigerian nation) if the public face mask use strategy is complemented with a social-distancing strategy. The community lockdown measures implemented in Nigeria on March 30, 2020 need to be maintained for at least three to four months to lead to the effective containment of COVID-19 outbreaks in the country. Relaxing, or fully lifting, the lockdown measures sooner, in an effort to re-open the economy or the country, may trigger a deadly second wave of the pandemic.

Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have recently been reported in many countries. These have exacerbated the coronavirus disease 2019 (COVID-19)-induced global health threats and hindered COVID-19 vaccine development and therapeutic progress. This commentary discusses the potential risk of the newly classified Mu variant of interest, seeming a highly vaccine-resistant variant, and the approaches that can be adopted to tackle this variant based on the available evidence. The SARS-CoV-2 B.1.621 (Mu variant) lineage has shown approximately ten times higher resistance to neutralizing sera obtained from COVID-19 survivors or BNT161b2-vaccinated people than the parenteral B.1 lineage. Several urgent and long-term strategic plans, including quick genomic surveillance for uncovering the genetic characteristics of the variants, equitable global mass vaccination, booster dose administration if required, and strict implementation of public health measures or non-pharmaceutical interventions, must be undertaken concertedly to restrict further infections, mutations, or recombination of the SARS-CoV-2 virus and its deadly strains.

The Korean government’s public health responses to the COVID-19 epidemic have achieved a remarkable outcome in terms of the measured number of infected patients and the overall mortality rate. Nonetheless, the public health authority’s various mitigation strategies and vaccination efforts have faced several challenges primarily posed by politically motivated Christian fundamentalists and ultraconservative media’s distorted news framing in Korea. This paper examines how these conservative forces – both religious and political – have undermined the Korean public health authority’s various mitigation efforts and discusses how to address the problems from a public policy point of view. The paper argues that a comprehensive legal reform including the introduction of effective punitive damages in the media market is a necessary minimum to address some of these problems. [ABSTRACT FROM AUTHOR]

This paper uses a SEIR(D) model to analyse the time-varying transmission dynamics of the COVID-19 epidemic in Korea throughout its multiple stages of development. This multi-stage estimation of the model parameters offers a better model fit compared to the whole period analysis and shows how the COVID-19's infection patterns change over time, primarily depending on the effectiveness of the public health authority's non-pharmaceutical interventions (NPIs). This paper uses the SEIR(D) compartment model to simulate and estimate the parameters for three distinctive stages of the COVID-19 epidemic in Korea, using a manually compiled COVID-19 epidemic dataset for the period between 18 February 2020 and 08 February 2021. The paper identifies three major stages of the COVID-19 epidemic, conducts multi-stage estimations of the SEIR(D) model parameters, and carefully infers context-dependent meaning of the estimation results to help better understand the unique patterns of the transmission of the novel coronavirus (SARS-CoV-2) in each stage. The original SIR compartment model may produce a poor and even misleading estimation result if it is used to cover the entire period of the epidemic. However, if we use the model carefully in distinctive stages of the COVID-19 epidemic, we can find useful insights into the nature of the transmission of the novel coronavirus and the relative effectiveness of the government's non-pharmaceutical interventions over time. Identifies three distinctive waves of the COVID-19 epidemic in Korea. Conducts multi-stage estimations of the COVID-19 transmission dynamics using SEIR(D) epidemic models. The transmission dynamics of the COVID-19 vary over time, primarily depending on the relative effectiveness of the government's non-pharmaceutical interventions (NPIs). The SEIR(D) epidemic model is useful and informative, but only when it is used carefully to account for the presence of multiple waves and context-dependent infection patterns in each wave. [ABSTRACT FROM AUTHOR]

The paper explores the idea that the success of the Korean government's non-pharmaceutical interventions in response to the COVID-19 epidemic can be better understood through the lens of industrial policy framework than many descriptive public policy literatures that have merely focused on administrative efficiency. It is emphasized in this paper that the Korean government has maintained sustained R&D support, tax subsidy, and various forms of public–private partnerships to help nurture and grow domestic infant industry in such strategic industrial areas as information-communication technology, biotechnology and health care, and pharmaceutical industry for a long time, and this soft industrial policy has enabled the public health authority to implement a series of successful non-pharmaceutical public health measures to suppress and mitigate the spread of the novel coronavirus. [ABSTRACT FROM AUTHOR]

Introduction: Many countries with an early outbreak of SARS-CoV-2 struggled to gauge the size and start date of the epidemic mainly due to limited testing capacities and a large proportion of undetected asymptomatic and mild infections. Iran was among the first countries with a major outbreak outside China. Methods: We constructed a globally representative sample of 802 genomes, including 46 samples from patients inside or with a travel history to Iran. We then performed a phylogenetic analysis to identify clades related to samples from Iran and estimated the start of the epidemic and early doubling times in cases. We leveraged air travel data from 36 exported cases of COVID-19 to estimate the point-prevalence and the basic reproductive number across the country. We also analysed the province-level all-cause mortality data during winter and spring 2020 to estimate under-reporting of COVID-19-related deaths. Finally, we use this information in an SEIR model to reconstruct the early outbreak dynamics and assess the effectiveness of intervention measures in Iran. Results: By identifying the most basal clade that contained genomes from Iran, our phylogenetic analysis showed that the age of the root is placed on 2019-12-21 (95 % HPD: 2019-09-07 – 2020-02-14). This date coincides with our estimated epidemic start date on 2019-12-25 (95 %CI: 2019-12-11 – 2020-02-24) based air travel data from exported cases with an early doubling time of 4.0 (95 %CI: 1.4–6.7) days in cases. Our analysis of all-cause mortality showed 21.9 (95 % CI: 16.7–27.2) thousand excess deaths by the end of summer. Our model forecasted the second epidemic peak and suggested that by 2020-08-31 a total of 15.0 (95 %CI: 4.9–25.0) million individuals recovered from the disease across the country. Conclusion: These findings have profound implications for assessing the stage of the epidemic in Iran despite significant levels of under-reporting. Moreover, the results shed light on the dynamics of SARS-CoV-2 transmissions in Iran and central Asia. They also suggest that in the absence of border screening, there is a high risk of introduction from travellers from areas with active outbreaks. Finally, they show both that well-informed epidemic models are able to forecast episodes of resurgence following a relaxation of interventions, and that NPIs are key to controlling ongoing epidemics.

Stay-at-home orders, physical distancing, face masks and other non-pharmaceutical interventions (NPIs) do not only impact COVID-19, but also the dynamics of various other infectious diseases. Bronchiolitis is a clinically diagnosed viral infection of the lower respiratory tract, and causes a yearly seasonal wave of admissions in paediatric wards worldwide. We counted 92,5% less bronchiolitis hospitalisations in Antwerp before the expected end of the peak this year (of which only 1 RSV positive), as compared to the last 3 years. Furthermore, there was a >99% reduction in the number of registered RSV cases in Belgium. Conslusion: The 2020 winter bronchiolitis peak is hitherto nonexistent, but we fear a 'delayed' spring/summer bronchiolitis peak when most NPIs will be relaxed and pre-pandemic life restarts. What is known? • Bronchiolitis causes a yearly seasonal wave of admissions in paediatric departments worldwide. • Non-pharmaceutical interventions (NPIs) do not only impact COVID-19, but also the dynamics of various other infectious diseases. What is new? • The 2020 winter bronchiolitis peak is hitherto nonexistent. • A 'delayed' spring or summer bronchiolitis peak could happen when most NPIs will be relaxed and pre-pandemic life restarts. [ABSTRACT FROM AUTHOR]

On 11 March 2020, the WHO declared the COVID-19 epidemic to be a global pandemic. This was a consequence of the rapid increase in the number of people with positive test results, the increase in deaths due to COVID-19, and the lack of pharmaceutical drugs. Governments introduced national lockdowns, which have impacted both energy consumption and economies. The purpose of this paper is to answer the following question: do COVID-19 lockdowns affect the business cycle? We used the cycle clock approach to assess the magnitude of decrease in electricity consumption in the three waves of the epidemic, namely, April 2020, November 2021, and April 2021. Additionally, we checked the relation between energy consumption and GDP by means of spectral analysis. Results for selected 28 European countries confirm an impact of the introduced non-pharmaceutical interventions on both energy consumption and business cycle. The reduction of restrictions in subsequent pandemic waves increased electricity consumption, which suggests movement out of the economic recession.

• We assess COVID-19 lockdowns' effects on Chilean businesses (2020–2021). • Lockdowns reduced sales, affecting MSMEs and select industries. • Vaccination campaign and mobility pass mitigated negative effects. • Targeted support needed for MSMEs and vulnerable industries affected by NPIs. • Post-vaccine, easing mobility restrictions improved economic recovery. This study evaluates the effects of COVID-19 lockdowns, differentiated by their stringency, on the sales of Chilean businesses across various size categories and industries throughout 2020 and 2021. It also explores the role of the vaccination campaign and the implementation of the Mobility Pass in mitigating the negative economic effects of stringent containment measures. The study uses administrative data from the Chilean Internal Revenue Service (SII), examining sales across different business sizes and industries, from March 2020 to December 2021. Through an econometric analysis, we estimate the effects of lockdowns on business sales during two distinct periods: initial reliance on dynamic non-pharmaceutical interventions (NPIs) pre-vaccine, and a subsequent stage characterized by high vaccine uptake and reduced NPI stringency. Lockdowns significantly reduced sales across all business sizes and most industries during the first period, with microenterprises and certain service sectors experiencing the highest decline. The national vaccination campaign and the introduction of the Mobility Pass in the second period appears to have mitigated the negative effects of lockdowns, primarily benefiting micro and small firms. The study highlights the trade-offs between health and economic outcomes during the pandemic, stressing the importance to alleviate mobility restrictions post-vaccine rollout to ease the economic strain on businesses. The findings call for targeted support measures for MSMEs and vulnerable industries affected by NPIs. [ABSTRACT FROM AUTHOR]

This study utilized modeling and simulation to examine the effectiveness of current and potential future COVID-19 response interventions in the West African countries of Guinea, Liberia, and Sierra Leone. A comparison between simulations can highlight which interventions could have an effect on the pandemic in these countries. An extended compartmental model was used to run simulations incorporating multiple vaccination strategies and non-pharmaceutical interventions (NPIs). In addition to the customary categories of susceptible, exposed, infected, and recovered (SEIR) compartments, this COVID-19 model incorporated early and late disease states, isolation, treatment, and death. Lessons learned from the 2014–2016 Ebola virus disease outbreak—especially the optimization of each country’s resource allocation—were incorporated in the presented models. For each country, models were calibrated to an estimated number of infections based on actual reported cases and deaths. Simulations were run to test the potential future effects of vaccination and NPIs. Multiple levels of vaccination were considered, based on announced vaccine allocation plans and notional scenarios. Increased vaccination combined with NPI mitigation strategies resulted in thousands of fewer COVID-19 infections in each country. This study demonstrates the importance of increased vaccinations. The levels of vaccination in this study would require substantial increases in vaccination supplies obtained through national purchases or international aid. While this study does not aim to develop a model that predicts the future, it can provide useful information for decision-makers in low- and middle-income nations. Such information can be used to prioritize and optimize limited available resources for targeted interventions that will have the greatest impact on COVID-19 pandemic response.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lokonon, Montcho, Klingler, Tovissodé, Glèlè Kakaï and Wolkewitz.)

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.

Non-pharmaceutical interventions (NPIs) used to limit SARS-CoV-2 transmission vary in their feasibility, appropriateness and effectiveness in different contexts. In Bangladesh a national lockdown implemented in March 2020 exacerbated poverty and was untenable long-term. A resurgence in 2021 warranted renewed NPIs. We sought to identify NPIs that were feasible in this context and explore potential synergies between interventions. We developed an SEIR model for Dhaka District, parameterised from literature values and calibrated to data from Bangladesh. We discussed scenarios and parameterisations with policymakers with the aid of an interactive app. These discussions guided modelling of lockdown and two post-lockdown measures considered feasible to deliver; symptoms-based household quarantining and compulsory mask-wearing. We compared NPI scenarios on deaths, hospitalisations relative to capacity, working days lost, and cost-effectiveness. Lockdowns alone were predicted to delay the first epidemic peak but could not prevent overwhelming of the health service and were costly in lost working days. Impacts of post-lockdown interventions depended heavily on compliance. Assuming 80% compliance, symptoms-based household quarantining alone could not prevent hospitalisations exceeding capacity, whilst mask-wearing prevented overwhelming health services and was cost-effective given masks of high filtration efficiency. Combining masks with quarantine increased their impact. Recalibration to surging cases in 2021 suggested potential for a further wave in 2021, dependent on uncertainties in case reporting and immunity. Masks and symptoms-based household quarantining synergistically prevent transmission, and are cost-effective in Bangladesh. Our interactive app was valuable in supporting decision-making, with mask-wearing being mandated early, and community teams being deployed to support quarantining across Dhaka. These measures likely contributed to averting the worst public health impacts, but delivering an effective response with consistent compliance across the population has been challenging. In the event of a further resurgence, concurrent messaging to increase compliance with both mask-wearing and quarantine is recommended. • We developed an SEIR model to compare feasible COVID-19 interventions in Bangladesh. • Masks and symptoms-based quarantine synergistically reduce SARS-CoV-2 transmission. • These combined interventions are cost-effective, assuming high-filtration efficiency masks. • Our interactive app was a useful tool in communicating epidemiology to policymakers. [ABSTRACT FROM AUTHOR]

Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have recently been reported in many countries. These have exacerbated the coronavirus disease 2019 (COVID-19)-induced global health threats and hindered COVID-19 vaccine development and therapeutic progress. This commentary discusses the potential risk of the newly classified Mu variant of interest, seeming a highly vaccine-resistant variant, and the approaches that can be adopted to tackle this variant based on the available evidence. The SARS-CoV-2 B.1.621 (Mu variant) lineage has shown approximately ten times higher resistance to neutralizing sera obtained from COVID-19 survivors or BNT161b2-vaccinated people than the parenteral B.1 lineage. Several urgent and long-term strategic plans, including quick genomic surveillance for uncovering the genetic characteristics of the variants, equitable global mass vaccination, booster dose administration if required, and strict implementation of public health measures or non-pharmaceutical interventions, must be undertaken concertedly to restrict further infections, mutations, or recombination of the SARS-CoV-2 virus and its deadly strains.

Background: New variants of SARS-CoV-2 are constantly discovered. Administration of COVID-19 vaccines and booster doses, combined with the application of non-pharmaceutical interventions (NPIs ) , is often used to prevent outbreaks of emerging variants. Such outbreak dynamics are further complicated by the population's behavior and demographic composition. Hence, realistic simulations are needed to estimate the efficiency of proposed vaccination strategies in conjunction with NPIs., Methods: We developed an individual-based model of COVID-19 dynamics that considers age-dependent parameters such as contact matrices, probabilities of symptomatic and severe disease, and households' age distribution. As a case study, we simulate outbreak dynamics under the demographic compositions of two Israeli cities with different household sizes and age distributions. We compare two vaccination strategies: vaccinate individuals in a currently prioritized age group, or dynamically prioritize neighborhoods with a high estimated reproductive number. Total infections and hospitalizations are used to compare the efficiency of the vaccination strategies under the two demographic structures, in conjunction with different NPIs., Results: We demonstrate the effectiveness of vaccination strategies targeting highly infected localities and of NPIs actively detecting asymptomatic infections. We further show that different optimal vaccination strategies exist for each sub-population's demographic composition and that their application is superior to a uniformly applied strategy., Conclusion: Our study emphasizes the importance of tailoring vaccination strategies to subpopulations' infection rates and to the unique characteristics of their demographics (e.g., household size and age distributions). The presented simulation framework and findings can help better design future responses against the following emerging variants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer RT declared a past co-authorship with the author UO to the handling editor., (Copyright © 2022 Ben-Zuk, Daon, Sasson, Ben-Adi, Huppert, Nevo and Obolski.)