Available via license: CC BY-NC 4.0
Content may be subject to copyright.
A preview of the PDF is not available
Assessing Mandatory Stay‐at‐Home and Business Closure Effects on the Spread of COVID‐19
Abstract
Background and Aims
The most restrictive non‐pharmaceutical interventions (NPIs) for controlling the spread of COVID‐19 are mandatory stay‐at‐home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).
Methods
We first estimate COVID‐19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden, and the US. Using first‐difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, two countries that did not implement mandatory stay‐at‐home and business closures, as comparison countries for the other 8 countries (16 total comparisons).
Results
Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a non‐significant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, e.g., the effect of mrNPIs was +7% (95CI ‐5%‐19%) when compared with Sweden, and +13% (‐12%‐38%) when compared with South Korea (positive means pro‐contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons.
Conclusions
While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.
... Suecia no llega a las buenas cifras de Alemania, a causa de los fallecidos en las residencias de mayores. Según el estudio liderado por (Bendavid et, al. 2021) cuatro de cada cinco muertes observadas en Suecia se dieron en residencias de mayores, otorgando tan solo un 2% de exceso de mortalidad, si no se hubiera descuidado este frente. ...
... Si comparamos los de exceso de mortalidad de los países en el periodo marzo -mayo, fase de mayor cierre en España, no se encuentran beneficios adicionales asociados a las medidas de confinamiento general. Este resultado es consistente con otros estudios previos realizados (Bendavid 2021). ...
... Suecia si bien se sitúa con más nota que España, no alcanza el óptimo. Esto es debido a que no consiguió aislar adecuadamente a los mayores en las residencias de ancianos en la primera ola (Bendavid 2021) tal y como paso en nuestro país. En esta línea, si España tuviera la tasa de mortalidad de Alemania o Suecia, se hubieran salvado miles de vidas. ...
La capacidad de adaptación y resistencia del coronavirus, con sus constantes mutaciones, está poniendo a prueba los sistemas sanitarios y las políticas públicas de los gobiernos en Europa. La duración y la severidad de la pandemia hacen necesario aprender de las experiencias de otros países, que parecen afrontar las crisis sanitarias con mejores resultados. En este artículo analizamos las estrategias e indicadores sanitarios de dos los países más innovadores, Alemania y Suecia. El estudio parece confirmar que la flexibilidad en sus procedimientos permite ajustarse mejor a las características del virus.
... Second, our results offer an explanation for recent unanticipated findings regarding mitigation strategies. Recent studies find lower-than-anticipated effectiveness of mitigation policies like stay-at-home orders in curbing the pandemic's spread (e.g., Herby et al. 2022;Bendavid et al. 2021;Reinbold 2021;Gupta et al. 2020). Our results suggest an unnoticed role of price-gouging regulations-increasing social contact and undermining mitigation-behind these surprising findings. ...
Despite long-standing criticisms, restrictions on price increases during emergencies remain widespread in the US. Criticisms most often cite the social costs of the shortages, but, we have found another, as yet unknown, cost: price-gouging regulations increased social contact during the onset of the COVID-19 pandemic. During the pandemic, thirty-four US states declared emergencies, which activated their preexisting price-gouging regulations, and eight others introduced new regulation along with their emergency declarations. Because these states border eight others that also declared emergencies, but had no price-gouging regulations, this created a unique natural experiment. Exploiting the pandemic-induced variation in regulation, and cellphone mobility data, we find that price controls increased visits to, and social contact in, commercial spaces, presumably because the regulation-induced shortages forced consumers to visit more stores and come in contact with more people as they struggled to find what they needed. This, of course, undermines social distancing efforts.
... These issues often concerned nonpharmaceutical interventions (NPIs), and included inter alia, mask effectiveness, school closures, modes of transmission, vaccine mandates and stay-at-home orders. [23][24][25][26][27] Disagreements were aired publicly, with regular media commentary from experts in different disciplines on how policy makers should respond to evidence. ...
It is common for aspects of the COVID-19 response—and other public health initiatives before it—to be described as polarised. Public health decisions emerge from an interplay of facts, norms and preferred courses of action. What counts as ‘evidence’ is diverse and contestable, and disagreements over how it should be interpreted are often the product of differing choices between competing values. We propose a definition of polarisation for the context of public health expertise that acknowledges and accounts for epistemic and social values as part of evidence generation and its application to public health practice. The ‘polarised’ label should be used judiciously because the descriptor risks generating or exacerbating the problem by oversimplifying complex issues and positions and creating groups that seem dichotomous. ‘Independence’ as a one-size-fits-all answer to expert polarisation is insufficient; this solution is premised on a scientistic account of the role of evidence in decision making and does not make room for the value difference that is at the heart of both polarisation and evidence-based decision making.
... On the declaration of a public health emergency of international concern (PHEIC) in response to the COVID-19 pandemic in March 2020, governments around the world adopted an array of measures intended to control transmission, some of which far exceeded the recommendations of the World Health Organization's (WHO's) Strategic and Technical Advisory Group on Infectious Hazards (STAG-IH) regarding personal protective hygiene, in controlling the progression of the pandemic [13][14][15][16]. Others have concluded that NPIs have been surprisingly ineffective [17][18][19][20][21][22][23]. Therefore, we recognise that there is an ongoing debate over the relative effectiveness of the various NPIs. ...
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.
... Compared to COVID-19 economic, infection phobia, and grief-related stressors, lockdown stress appears to have the greatest impact on executive function deficiencies and mental health. According to a study of the lockdown, similar reductions may be possible with less restrictive interventions, despite the lockdown's small benefits (Bendavid et al., 2021). Lockdown had the worse emotional and cognitive effects on the Kuwaiti COVID-19 experience. ...
The purpose of this study is to investigate the differential impact of various COVID-19 stressors (economic, infection fears, grief, and lockdown stressors) and their cumulative impact on peri-post-COVID-19 syndrome. Peri-post-COVID-19 syndrome (PPCS) is a mental health and cognitive syndrome associated with chronic traumatic stress, particularly COVID-19. The sample consisted of 490 Kuwaiti citizens aged 18–60 years ( M = 24.97, SD = 9.10), with 66.3% being female. Data were collected from October 2021 to January 2022. We assessed how individuals felt about COVID-19 stressors, cumulative traumatic events and stressors, complex PTSD (CPTSD), PTSD, anxiety, depression, and executive functions. A structural equation was used to test the differential and cumulative impact of COVID-19 stressors. COVID-19 cumulative stressors, especially lockdown, had the strongest correlation with CPTSD. The highest variance was accounted for by lockdown stressors ( R ² = .752). COVID-19 cumulative stressors had a medium-to-large effect on PPCS. In the affluent Kuwaiti context, lockdown stressors appear to have a greater impact on mental health and executive dysfunction than other COVID-19 stressors. In the PPCS, CPTSD appears to be the most robust outcome variable. Conceptually, the study provided preliminary evidence of the PPCS and associated cognitive deficits as powerful drivers for COVID-19 and of continuous/prolonged traumatic stress for COVID-19. The study highlighted the need for innovation in developing multiparameter intervention strategies with a pericognitive and cognitive training component to address the multiple impacts of the pandemic.
... Initially, the pandemic was controlled by non-pharmacological interventions (NPIs) like masking or containments, while many researchers argued that NPIs had either little effect (Bendavid et al., 2021) or that policymakers were unable to weigh up costs and benefits of these NPIs properly (Lewis, 2022). One year later, from early 2021, the world has access to vaccines, but national coverage rates vary widely from country to country. ...
Quite strikingly, there is significant variation in Covid-19 vaccine coverage around the world. Some countries do not progress from around 2-3% while others are close to 100% coverage. In addition to some already known economic, health and sociodemographic predictors, the present research is interested in emotional factors that may predict a significant part of this crosscountry variation. We examined the personality factor Neuroticism, which corresponds to the relatively stable tendency to experience negative emotions, anxiety and low tolerance for stress. Results confirm that gross domestic product represents around 50 percent of crosscountry variation. Neuroticism added 6 to 9 percent of inter-country variation in vaccination coverage. The results are discussed in relation to the associations between Neuroticism, increased worry, greater attention to Covid-19 related information and confidence, as well as lower vaccine hesitancy. Public Access: https://rdcu.be/c3S6M
Background:
The objectives of this systematic review were to synthesize qualitative evidence on the impacts of COVID-19 restrictions on physical activity (PA) for children and youth, and explore factors perceived to influence those impacts.
Methods:
Five databases (MEDLINE, Embase, SPORTDiscus, ERIC, and CINAHL) were searched initially in June 2021 and updated in December 2021 to locate qualitative articles considering COVID-19 restrictions and PA for children and youth (≤18 y old), in any setting. Eligibility, quality assessments, and data extraction were completed by 2 independent reviewers. Data were synthesized using meta-aggregation with confidence of findings rated using ConQual.
Results:
After screening 3505 records, 15 studies were included. Curriculum-based PA, organized sport, and active transportation were negatively impacted by COVID-19 restrictions. Negative changes were affected by COVID-19 exposure risks, inadequate instruction, poor access, screen time, and poor weather. Unstructured PA was inconsistently impacted; outdoor unstructured PA increased for some. Positive changes were facilitated by family co-participation, availability of outdoor space, and perceived mental health benefits.
Conclusion:
Qualitative data indicated restrictions had a predominantly negative impact on PA for children and youth, but inconsistent impacts on unstructured PA. The improved contextual understanding offered by our review will be foundational knowledge for health strategies moving forward.
Article 5 of the European Convention on Human Rights enshrines the right to liberty, one of the oldest and most fundamental rights in the human rights tradition, and one of the core rights in the Convention. Central to the judicial understanding of Article 5 is the ‘exhaustive justification principle’: unlike with other rights, such as the right to privacy, interferences with liberty can only be justified by one of the specific reasons listed in Article 5 itself. This article shows that this rigidity has posed problems in practice: faced with modern developments unforeseeable at the time of the Convention's writing, such as the use of novel policing techniques and the COVID-19 pandemic, judges have interpreted Article 5 in an unusual and artificial way, sacrificing the exhaustive justification principle in doing so, in order to achieve sensible outcomes. The integrity of Article 5 has been threatened, with serious consequences for the future protection of the right to liberty. This trend is explained, evidenced and evaluated, and some (partial) solutions and concessions are considered.
Mitigation measures included primarily lockdowns and masks and, later in the pandemic, mass vaccination. All of them were supposed to eradicate the disease or at least to “flatten the curve.” To stress the need for disease eradication and/or the need for reduced transmission rates, three postulates were put forward by the proponents of the pandemic policy responses. First, it was claimed that the virus poses a high death risk to all age-groups, and so we need policies that will be able to offer protection to all people. This is the first postulate, which I would like to call the “equal vulnerability thesis.” Second, the claim that there is no pre-existing immunity and hence all people are equally susceptible to the virus, which is the “equal susceptibility thesis.” The third postulate is that the coronavirus can be transmitted not only by symptomatic but also by asymptomatic people. This is the “equal infectivity thesis.” These three premises were mistaken, and the pandemic policies, i.e., lockdowns, masks, and mass vaccination, failed to achieve their declared goals, i.e., they did not eradicate the disease and they did not impact on transmission rates.
Containing a pandemic is first and foremost a management problem: one has to find ways to reduce mobility and physical contacts in order to slow down the spread of the virus. We discuss and construct a novel database of internal and external lockdown measures around the world and analyze whether they helped reduce the spread of infections and the number of deaths. We address the endogeneity of lockdowns by modeling anticipation effects. Our data cover 178 countries in the period from December 2019 to November 2020 and identify lockdown and release periods along with confirmed cases of infections and deaths resulting from COVID-19. Overall, we find that lockdowns were effective, reduced mobility, and saved about 3.6 million lives in developed countries within 100 days after they were implemented. Measures taken within countries (rather than border closure) and partial lockdowns (instead of more constraining measures) were the most effective. However, in developing countries, where the opportunity cost of staying home might be too high for people to comply, lockdowns were ineffective. Additionally, the release of lockdown measures, which started in mid-May 2020 in most countries, did not lead to a strong resurgence of the virus except for border closure releases.
This paper was accepted by Stefan Scholtes, healthcare management.
Supplemental Material: The data is available at https://doi.org/10.1287/mnsc.2022.4652 .
The ability to preferentially protect high-risk groups in COVID-19 is hotly debated. Here, the aim is to present simple metrics of such precision shielding of people at high risk of death after infection by SARS-CoV-2; demonstrate how they can estimated; and examine whether precision shielding was successfully achieved in the first COVID-19 wave. The shielding ratio, S, is defined as the ratio of prevalence of infection among people in a high-risk group versus among people in a low-risk group. The contrasted risk groups examined here are according to age (≥70 vs <70 years), and institutionalised (nursing home) setting. For age-related precision shielding, data were used from large seroprevalence studies with separate prevalence data for elderly versus non-elderly and with at least 1000 assessed people≥70 years old. For setting-related precision shielding, data were analysed from 10 countries where information was available on numbers of nursing home residents, proportion of nursing home residents among COVID-19 deaths and overall population infection fatality rate (IFR). Across 17 seroprevalence studies, the shielding ratio S for elderly versus non-elderly varied between 0.4 (substantial shielding) and 1.6 (substantial inverse protection, that is, low-risk people being protected more than high-risk people). Five studies in the USA all yielded S=0.4–0.8, consistent with some shielding being achieved, while two studies in China yielded S=1.5–1.6, consistent with inverse protection. Assuming 25% IFR among nursing home residents, S values for nursing home residents ranged from 0.07 to 3.1. The best shielding was seen in South Korea (S=0.07) and modest shielding was achieved in Israel, Slovenia, Germany and Denmark. No shielding was achieved in Hungary and Sweden. In Belgium (S=1.9), the UK (S=2.2) and Spain (S=3.1), nursing home residents were far more frequently infected than the rest of the population. In conclusion, the experience from the first wave of COVID-19 suggests that different locations and settings varied markedly in the extent to which they protected high-risk groups. Both effective precision shielding and detrimental inverse protection can happen in real-life circumstances. COVID-19 interventions should seek to achieve maximal precision shielding.
OBJECTIVE
To examine whether the age distribution of COVID-19 deaths and the share of deaths in nursing homes changed in the second versus the first pandemic wave.
ELIGIBLE DATA
We considered all countries that had at least 4000 COVID-19 deaths occurring as of November 25, 2020, at least 200 COVID-19 deaths occurring in the first wave period, and at least 200 COVID-19 deaths occurring in the second wave period; and which had sufficiently detailed information available on the age distribution of these deaths. We also considered countries with data available on COVID-19 deaths of nursing home residents for the two waves.
MAIN OUTCOME MEASURES
Change in the second wave versus the first wave in the proportion of COVID-19 deaths occurring in people <50 years old among all COVID-19 deaths and among COVID019 deaths in people <70 years old; and change in the proportion of COVID-19 deaths in nursing home residents among all COVID-19 deaths.
RESULTS
Data on age distribution in eligible locations were available for 11 countries. Individuals <50 years old tended to have a larger share in the total COVID-19 deaths in the second wave than in the first wave in western European countries and the USA, but the absolute difference did not exceed 0.5% in any country. The proportion of deaths in individuals <50 years old was higher in Turkey and Ukraine, but it decreased in the second wave. Separate data on nursing home COVID-19 deaths for first and second waves were available for 9 countries. With the exception of Australia, the share of COVID-19 deaths that were accounted by nursing home residents decreased in the second wave, and the decrease was significant and substantial (relative risk estimates: 0.28 to 0.78) in 7/9 countries.
CONCLUSIONS
In the examined countries, age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities has decreased in most countries in the second wave.
What is known on this topic
* COVID-19 risk of death has a very steep age gradient
* Many COVID-19 deaths occur in nursing home residents
* Many countries have seen a pattern of two separate waves of COVID-19, but it is unknown whether these two waves differ in the age distribution of COVID-19 deaths and in fatalities in nursing home residents
What this study adds
* Age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave in most countries, with some exceptions.
* Deaths in people <50 years old remain a small minority of COVID-19 deaths.
* The contribution of deaths in nursing home residents to total fatalities remains high in absolute magnitude, but it has decreased in most countries in the second wave.
Time and intimacy drive transmission
A minority of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmit most infections. How does this happen? Sun et al. reconstructed transmission in Hunan, China, up to April 2020. Such detailed data can be used to separate out the relative contribution of transmission control measures aimed at isolating individuals relative to population-level distancing measures. The authors found that most of the secondary transmissions could be traced back to a minority of infected individuals, and well over half of transmission occurred in the presymptomatic phase. Furthermore, the duration of exposure to an infected person combined with closeness and number of household contacts constituted the greatest risks for transmission, particularly when lockdown conditions prevailed. These findings could help in the design of infection control policies that have the potential to minimize both virus transmission and economic strain.
Science , this issue p. eabe2424
Importance
United States primary school closures during the 2020 coronavirus disease 2019 (COVID-19) pandemic affected millions of children, with little understanding of the potential health outcomes associated with educational disruption.
Objective
To estimate the potential years of life lost (YLL) associated with the COVID-19 pandemic conditioned on primary schools being closed or remaining open.
Design, Setting, and Participants
This decision analytical model estimated the association between school closures and reduced educational attainment and the association between reduced educational attainment and life expectancy using publicly available data sources, including data for 2020 from the US Centers for Disease Control and Prevention, the US Social Security Administration, and the US Census Bureau. Direct COVID-19 mortality and potential increases in mortality that might have resulted if school opening led to increased transmission of COVID-19 were also estimated.
Main Outcomes and Measures
Years of life lost.
Results
A total of 24.2 million children aged 5 to 11 years attended public schools that were closed during the 2020 pandemic, losing a median of 54 (interquartile range, 48-62.5) days of instruction. Missed instruction was associated with a mean loss of 0.31 (95% credible interval [CI], 0.10-0.65) years of final educational attainment for boys and 0.21 (95% CI, 0.06-0.46) years for girls. Summed across the population, an estimated 5.53 million (95% CI, 1.88-10.80) YLL may be associated with school closures. The Centers for Disease Control and Prevention reported a total of 88 241 US deaths from COVID-19 through the end of May 2020, with an estimated 1.50 million (95% CI, 1.23-1.85 million) YLL as a result. Had schools remained open, 1.47 million (95% credible interval, 0.45-2.59) additional YLL could have been expected as a result, based on results of studies associating school closure with decreased pandemic spread. Comparing the full distributions of estimated YLL under both “schools open” and “schools closed” conditions, the analysis observed a 98.1% probability that school opening would have been associated with a lower total YLL than school closure.
Conclusions and Relevance
In this decision analytical model of years of life potentially lost under differing conditions of school closure, the analysis favored schools remaining open. Future decisions regarding school closures during the pandemic should consider the association between educational disruption and decreased expected lifespan and give greater weight to the potential outcomes of school closure on children’s health.
Background
The ability to preferentially protect high-groups in COVID-19 is hotly debated. Here, the aim is to present simple metrics of such precision shielding of people at high-risk of death after infection by SARS-CoV-2; demonstrate how they can estimated; and examine whether precision shielding was successfully achieved in the first COVID-19 wave.
Methods
The shielding ratio, S, is defined as the ratio of prevalence of infection among people at a high-risk group versus among people in a low-risk group. The contrasted risk groups examined here are according to age (>=70 versus <70 years), and institutionalized (nursing home) setting. For age-related precision shielding, data were used from large seroprevalence studies with separate prevalence data for elderly versus non-elderly and with at least 1000 assessed people >=70 years old. For setting-related precision shielding, data were analyzed from 10 countries where information was available on numbers of nursing home residents, proportion of nursing home residents among COVID-19 deaths, and overall population infection fatality rate.
Findings
Across 17 seroprevalence studies, the shielding ratio S for elderly versus non-elderly varied between 0.4 (substantial shielding) and 1.6 (substantial inverse protection, i.e. low-risk people being protected more than high-risk people). Five studies in USA all yielded S=0.4-0.8, consistent with some shielding being achieved, while two studies in China yielded S=1.5-1.6, consistent with inverse protection. Assuming 25% infection fatality rate among nursing home residents, S values for nursing home residents ranged from 0.07 to 3.1. The best shielding was seen in South Korea (S=0.07) and modest shielding was achieved in Israel, Slovenia, Germany, and Denmark. No shielding was achieved in Hungary and Sweden. In Belgium (S=1.9), UK (S=2.2) and Spain (S=3.1), nursing home residents were far more frequently infected that the rest of the population.
Interpretation
The experience from the first wave of COVID-19 suggests that different locations and settings varied markedly in the extent to which they protected high-risk groups. Both effective precision shielding and detrimental inverse protection can happen in real-life circumstances. COVID-19 interventions should seek to achieve maximal precision shielding.
Introduction
Since the emergence of SARS-CoV-2, governments have implemented a combination of public health responses based on non-pharmaceutical interventions (NPIs), with significant social and economic consequences. Quantifying the efficiency of different NPIs implemented by European countries to overcome the first epidemic wave could inform preparedness for forthcoming waves.
Methods
We used a dataset compiled by the European Centre for Disease Control (ECDC) on daily COVID-19 incidence, mortality and NPI implementation in 32 European countries. We adapted a capture-recapture method to limit non-reporting bias in incidence data, which we fitted to an age-structured mathematical model coupled with Monte Carlo Markov Chain to quantify the efficiency of 258 public health responses (PHR, a combination of several NPIs) in reducing SARS-Cov-2 transmission rates. From these PHR efficiencies, we used time series analyses to isolate the effect of 13 NPIs at different levels of implementation (fully implemented vs. partially relaxed).
Results
Public health responses implemented in Europe led to a median decrease in viral transmission of 71%, enough to suppress the epidemic. PHR efficiency was positively associated with the number of NPIs implemented simultaneously. The largest effect among NPIs was observed for stay at home orders targeted at risk groups (β=0.24, 95%CI 0.16-0.32) and teleworking (β=0.23, 95%CI 0.15-0.31), followed by enforced stay at home orders for the general population, closure of non-essential businesses and services, bans on gatherings of 50 individuals or more, and closure of universities. Partial relaxation of most NPIs resulted in lower than average or non-significant changes in response efficiency.
Conclusion
This large-scale estimation of NPI and PHR efficiency against SARS-COV-2 transmission in Europe suggests that a combination of NPIs targeting different population groups should be favored to control future epidemic waves.
To limit the rapid spread of COVID-19, most governments have introduced different non-pharmaceutical interventions, which might have severe costs for society. Therefore, it is crucial to evaluate the most cost-effective interventions, using, for instance, Bayesian modelling. Such modelling efforts have deemed lockdown to account for 81% of the reduction in R 0 , contributing to government policies. Here, we show that these conclusions are unsupported and that policies therefore should not be based on these studies.
https://www.eurosurveillance.org/for-authors
OBJECTIVE
To examine whether the age distribution of COVID-19 deaths and the share of deaths in nursing homes changed in the second versus the first pandemic wave.
ELIGIBLE DATA
We considered all countries that had at least 4000 COVID-19 deaths occurring as of January 14, 2020, at least 200 COVID-19 deaths occurring in each of the two epidemic wave periods; and which had sufficiently detailed information available on the age distribution of these deaths. We also considered countries with data available on COVID-19 deaths of nursing home residents for the two waves.
MAIN OUTCOME MEASURES
Change in the second wave versus the first wave in the proportion of COVID-19 deaths occurring in people <50 years (“young deaths”) among all COVID-19 deaths and among COVID-19 deaths in people <70 years old; and change in the proportion of COVID-19 deaths in nursing home residents among all COVID-19 deaths.
RESULTS
Data on age distribution were available for 14 eligible countries. Individuals <50 years old had small absolute difference in their share of the total COVID-19 deaths in the two waves across 13 high-income countries (absolute differences 0.0-0.4%). Their proportion was higher in Ukraine, but it decreased markedly in the second wave. The odds of young deaths was lower in the second versus the first wave (summary prevalence ratio 0.81, 95% CI 0.71-0.92) with large between-country heterogeneity. The odds of young deaths among deaths <70 years did not differ significantly across the two waves (summary prevalence ratio 0.96, 95% CI 0.86-1.06). Eligible data on nursing home COVID-19 deaths were available for 11 countries. The share of COVID-19 deaths that were accounted by nursing home residents decreased in the second wave significantly and substantially in 8 countries (prevalence ratio estimates: 0.36 to 0.78), remained the same in Denmark and Norway and markedly increased in Australia.
CONCLUSIONS
In the examined countries, age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities has decreased in most countries in the second wave.
This study assesses the association of social distancing due to coronavirus disease 2019 (COVID-19) with immunizations administered by age category (0-2 years, 3-9 years, and 10-17 years) in Colorado.
Understanding the outbreak dynamics of the COVID-19 pandemic has important implications for successful containment and mitigation strategies. Recent studies suggest that the population prevalence of SARS-CoV-2 antibodies, a proxy for the number of asymptomatic cases, could be an order of magnitude larger than expected from the number of reported symptomatic cases. Knowing the precise prevalence and contagiousness of asymptomatic transmission is critical to estimate the overall dimension and pandemic potential of COVID-19. However, at this stage, the effect of the asymptomatic population, its size, and its outbreak dynamics remain largely unknown. Here we use reported symptomatic case data in conjunction with antibody seroprevalence studies, a mathematical epidemiology model, and a Bayesian framework to infer the epidemiological characteristics of COVID-19. Our model computes, in real time, the time-varying contact rate of the outbreak, and projects the temporal evolution and credible intervals of the effective reproduction number and the symptomatic, asymptomatic, and recovered populations. Our study quantifies the sensitivity of the outbreak dynamics of COVID-19 to three parameters: the effective reproduction number, the ratio between the symptomatic and asymptomatic populations, and the infectious periods of both groups. For nine distinct locations, our model estimates the fraction of the population that has been infected and recovered by Jun 15, 2020 to 24.15% (95% CI: 20.48%-28.14%) for Heinsberg (NRW, Germany), 2.40% (95% CI: 2.09%-2.76%) for Ada County (ID, USA), 46.19% (95% CI: 45.81%-46.60%) for New York City (NY, USA), 11.26% (95% CI: 7.21%-16.03%) for Santa Clara County (CA, USA), 3.09% (95% CI: 2.27%-4.03%) for Denmark, 12.35% (95% CI: 10.03%-15.18%) for Geneva Canton (Switzerland), 5.24% (95% CI: 4.84%-5.70%) for the Netherlands, 1.53% (95% CI: 0.76%-2.62%) for Rio Grande do Sul (Brazil), and 5.32% (95% CI: 4.77%-5.93%) for Belgium. Our method traces the initial outbreak date in Santa Clara County back to January 20, 2020 (95% CI: December 29, 2019–February 13, 2020). Our results could significantly change our understanding and management of the COVID-19 pandemic: A large asymptomatic population will make isolation, containment, and tracing of individual cases challenging. Instead, managing community transmission through increasing population awareness, promoting physical distancing, and encouraging behavioral changes could become more relevant.