Establishing an ad hoc COVID-19 mortality surveillance during the first epidemic wave in Belgium, 1 March to 21 June 2020

BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.AimTo document and assess the COVID-19 mortality surveillance in Belgium.MethodsWe described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.ResultsThe participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.ConclusionBelgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of ‘COVID-19-related deaths’ in a context of limited testing capacity has provided timely information about the severity of the epidemic.     

Estimates of mortality attributable to COVID-19: a statistical model for monitoring COVID-19 and seasonal influenza,Denmark, spring 2020

BackgroundTimely monitoring of COVID-19 impact on mortality is critical for rapid risk assessment and public health action.AimBuilding upon well-established models to estimate influenza-related mortality, we propose a new statistical Attributable Mortality Model (AttMOMO), which estimates mortality attributable to one or more pathogens simultaneously (e.g. SARS-CoV-2 and seasonal influenza viruses), while adjusting for seasonality and excess temperatures.MethodsData from Nationwide Danish registers from 2014-week(W)W27 to 2020-W22 were used to exemplify utilities of the model, and to estimate COVID-19 and influenza attributable mortality from 2019-W40 to 2020-W20.ResultsSARS-CoV-2 was registered in Denmark from 2020-W09. Mortality attributable to COVID-19 in Denmark increased steeply, and peaked in 2020-W14. As preventive measures and national lockdown were implemented from 2020-W12, the attributable mortality started declining within a few weeks. Mortality attributable to COVID-19 from 2020-W09 to 2020-W20 was estimated to 16.2 (95% confidence interval (CI): 12.0 to 20.4) per 100,000 person-years. The 2019/20 influenza season was mild with few deaths attributable to influenza, 3.2 (95% CI: 1.1 to 5.4) per 100,000 person-years.ConclusionAttMOMO estimates mortality attributable to several pathogens simultaneously, providing a fuller picture of mortality by COVID-19 during the pandemic in the context of other seasonal diseases and mortality patterns. Using Danish data, we show that the model accurately estimates mortality attributable to COVID-19 and influenza, respectively. We propose using standardised indicators for pathogen circulation in the population, to make estimates comparable between countries and applicable for timely monitoring.     

COVID-19 Mortality and Social Inequalities: Social inequalities in COVID-19 mortality by area and individual-level characteristics in Canada,January to July/August 2020: Results from two national data integrations

BackgroundDespite early reports of social determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) burden, national Canadian reporting on COVID-19 inequalities has been limited. The objective of this study is to describe inequalities in COVID-19 mortality in Canada using preliminary data, as part of the Pan-Canadian Health Inequalities Reporting Initiative.MethodsTwo provisional Canadian Vital Statistics Death Database integrations were used. Data concerning deaths between January 1 and July 4, 2020, among private-dwelling residents were linked to individual-level data from the 2016 short-form Census, and disaggregated by sex and low-income status, dwelling type, household type and size. Data concerning deaths between January 1 and August 31, 2020 linked to 2016 Census area data were disaggregated by sex and neighbourhood ethno-cultural composition quintiles (based on the proportion of residents who are recent immigrants, visible minorities, born outside of Canada, with no knowledge of English or French), income quintiles and urban residence. The COVID-19 age-standardized mortality rate (per 100,000 population) differences and ratios between groups were estimated.ResultsAs of July/August 2020, apartment dwellers, residents of urban centres, neighbourhoods with the highest ethno-cultural composition or lowest income experienced 14 to 30 more COVID-19-related deaths/100,000 compared with reference groups (residents of single-detached homes, outside of urban centres, with lowest ethno-cultural concentration or highest income, respectively). Per 100,000 population, sex/gender inequalities were also larger in these four groups (11 to 18 more male than female deaths) than in the reference groups (two to four more male than female deaths).ConclusionThese findings highlight how populations facing socioeconomic disadvantage have experienced a higher overall burden of deaths. Areas for future research are discussed to guide health equity-informed pandemic response.     

Real-time monitoring shows substantial excess all-cause mortality during second wave of COVID-19 in Europe,October to December 2020

The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.     

Excess mortality from COVID and non-COVID causes in minority populations

The 2020 US mortality totaled 2.8 million after early March, which is 17.3% higher than age-population–weighted mortality over the same time interval in 2017 to 2019, for a total excess death count of 413,592. We use data on weekly death counts by cause, as well as life tables, to quantify excess mortality and life years lost from both COVID-19 and non–COVID-19 causes by race/ethnicity, age, and gender/sex. Excess mortality from non–COVID-19 causes is substantial and much more heavily concentrated among males and minorities, especially Black, non-Hispanic males, than COVID-19 deaths. Thirty-four percent of the excess life years lost for males is from non–COVID-19 causes. While minorities represent 36% of COVID-19 deaths, they represent 70% of non–COVID-19 related excess deaths and 58% of non–COVID-19 excess life years lost. Black, non-Hispanic males represent only 6.9% of the population, but they are responsible for 8.9% of COVID-19 deaths and 28% of 2020 excess deaths from non–COVID-19 causes. For this group, nearly half of the excess life years lost in 2020 are due to non–COVID-19 causes.

Three distinct literatures about the COVID-19 pandemic provide the backdrop for this paper. The first documents that COVID-19 mortality is more heavily concentrated in male and minority populations (1–4). The second shows that the US death count in 2020 has exceeded expected deaths based on the recent historical average (henceforth, “excess” deaths) and that the COVID-19 death count does not entirely explain the gap, meaning deaths from non–COVID-19 causes contribute to above-average mortality in 2020 (5–7). The third literature translates 2020 excess mortality in the US to the life years lost from COVID-19 and non–COVID-19 causes (8–11). In this paper, we merge these three literatures by using data on vital statistics to examine the burden of excess mortality by race/ethnicity, age, and gender/sex. We then use life tables to translate deaths at particular ages into life years lost. As non–COVID-19 excess death rates are high among the young, the fraction of excess deaths that are from COVID-19 is larger than the fraction of life years lost from the virus alone. As non–COVID-19 excess mortality is much more common among males, minorities, and the young, we document that the life years lost from non–COVID-19 excess death is heavily concentrated in minority men.     

Obesity: A potential risk factor for infection and mortality in the current COVID-19 epidemic

Background and aimsCOVID-19 is an ongoing global pandemic, affecting nearly 35 million people from 214 countries as at September 30, 2020 and emerging evidence suggests that obesity is a potential risk factor for communicable diseases, including viral infections. Therefore, we investigated the relationship between obesity prevalence of the total adult population and COVID-19 infection and mortality rates, in different countries.MethodsA total of 54 countries from six continents were selected. Country-specific obesity prevalence data were retrieved from the latest non-communicable diseases profiles released by the Non-communicable Diseases and Mental Health Cluster of World Health Organization, while the real time statistics from the Worldometer website were used to extract data on COVID-19 infections and mortality per million of the total population as of September 30, 2020.ResultsObesity prevalence data ranged from 2.0% (Vietnam) to 35.0% (Saudi Arabia). Among the selected countries, the highest number of COVID-19 cases per million was documented in Qatar (n = 44,789) while the lowest was reported from Vietnam (n = 11). Highest mortality per million population due to COVID-19 infections occurred in Peru (n = 981), in contrast with the smallest number reported in Mongolia (n = 0). A significant positive correlation (r = 0.46; p < 0.001) was observed between the total number of COVID-19 infections and the prevalence of obesity. COVID-19 mortality was also significantly correlated (r = 0.34; p < 0.05) with the prevalence of obesity.ConclusionsObesity prevalence in each country was significantly associated with both infection and mortality rate of COVID-19.     

SARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut

BackgroundInfection fatality rate and infection hospitalization rate, defined as the proportion of deaths and hospitalizations, respectively, of the total infected individuals, can estimate the actual toll of coronavirus disease 2019 (COVID-19) on a community, as the denominator is ideally based on a representative sample of a population, which captures the full spectrum of illness, including asymptomatic and untested individuals.ObjectiveTo determine the COVID-19 infection hospitalization rate and infection fatality rate among the non-congregate population in Connecticut between March 1 and June 1, 2020.MethodsThe infection hospitalization rate and infection fatality rate were calculated for adults residing in non-congregate settings in Connecticut prior to June 2020. Individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies were estimated using the seroprevalence estimates from the recently conducted Post-Infection Prevalence study. Information on total hospitalizations and deaths was obtained from the Connecticut Hospital Association and the Connecticut Department of Public Health, respectively.ResultsPrior to June 1, 2020, nearly 113,515 (90% confidence interval [CI] 56,758-170,273) individuals were estimated to have SARS-CoV-2 antibodies, and there were 7792 hospitalizations and 1079 deaths among the non-congregate population. The overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% (90% CI, 4.58%-13.72%) and 0.95% (90% CI, 0.63%-1.90%), respectively, and there was variation in these rate estimates across subgroups; older people, men, non-Hispanic Black people, and those belonging to 2 of the counties had a higher burden of adverse outcomes, although the differences between most subgroups were not statistically significant.ConclusionsUsing representative seroprevalence estimates, the overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% and 0.95%, respectively, among community residents in Connecticut.     

Excesso de Mortalidade Hospitalar por Doenças Cardiovasculares no Brasil Durante o Primeiro Ano da Pandemia de COVID-19

Background:The COVID-19 pandemic has had an impact on mortality from several diseases worldwide, especially cardiovascular diseases (CVD). Brazil is a continent-sized country with significant differences in the health care structure between its federative units.Objective:Analyze in-hospital mortality from CVDs in the Brazilian public health system during the first year of the COVID-19 pandemic (2020).Methods:This is an ecological study analyzing the absolute number of in-hospital deaths and the rate of in-hospital mortality in Brazil, its macro-regions, and federative units. Data were obtained from the Hospital Information System of the Brazilian Ministry of Health. To analyze excess mortality, the P-score was used. It compares the events observed with those expected for a given place and period. The P-score was corrected by the joinpoint regression model, with a 95% confidence interval and 5% significance level.Results:There were 93,104 in-hospital deaths due to CVD in Brazil in 2020, representing 1,495 fewer deaths (P score: −1.58) than expected. The central-west region had a positive P-score, with a 15.1% increase in the number of deaths. Ten federative units showed a greater number of deaths in 2020. There was also a 13.3% excess in-hospital mortality at the country level, and an excess in-hospital mortality in all macro-regions.Conclusions:There was a decrease in the absolute number of in-hospital deaths, as well as an increase in in-hospital mortality from CVD in Brazil, in 2020, after the COVID-19 pandemic onset.     

Estimated number of deaths directly averted in people 60 years and older as a result of COVID-19 vaccination in the WHO European Region,December 2020 to November 2021

Since December 2019, over 1.5 million SARS-CoV-2-related fatalities have been recorded in the World Health Organization European Region - 90.2% in people ≥ 60 years. We calculated lives saved in this age group by COVID-19 vaccination in 33 countries from December 2020 to November 2021, using weekly reported deaths and vaccination coverage. We estimated that vaccination averted 469,186 deaths (51% of 911,302 expected deaths; sensitivity range: 129,851–733,744; 23–62%). Impact by country ranged 6–93%, largest when implementation was early.     

Analyzing COVID-19 pandemic for unequal distribution of tests,identified cases,deaths, and fatality rates in the top 18 countries

Background and aimsCOVID-19 pandemic has affected various countries differently due to variance in demographics, income level, health infrastructure, government response, control and enforcement, and cultural traits of different populations. This study aims to identify significant factors behind the unequal distribution of identified cases and deaths in different countries. Our study’s objective is comparative analysis and identification of relations between the spread of COVID-19 pandemic, population characteristics, and government response.MethodsThe top 18 countries worst hit by COVID-19 cases were identified. The data metrics, such as the number of cases, deaths, fatality rates, tests, average life expectancy, and population, were collected and consolidated.ResultsCountries with significant percentage of the older population are vulnerable to a high number of deaths due to COVID-19. Developed countries have higher per capita testing, whereas testing is less intensive in developing/underdeveloped countries. There is a consensus among health experts that COVID-19 has higher fatality rates for people above 60, however, with further age, this increases exponentially. Countries with higher life expectancy are also high-income countries, and the best course of action would be to provide specialized support to self-isolate for people of ages 75 and above.ConclusionThe behaviour of disease occurring at a large scale and interaction with different populations is studied to understand and differentiate the factors and measures that successfully inhibited the pandemic. The study benchmarks different countries based on their performance and efforts against the pandemic and provides some useful insights on the efficiency of their governance and potential to improve & ramp up their programs. The economic status and existing healthcare infrastructure as they are the key factors in determining the country’s ability to contain and minimize the losses from this pandemic.     

Are diabetes and its medications risk factors for the development of COVID-19? Data from a population-based study in Sicily

Background and aimsDiabetes mellitus (DM) has been associated with higher incidence of severe cases of COVID-19 in hospitalized patients, but it is unknown whether DM is a risk factor for the overall COVID-19 incidence. The aim of present study was to investigate whether there is an association of DM with COVID-19 prevalence and case fatality, and between different DM medications and risk for COVID-19 infection and death.Methods and resultsretrospective observational study on all SARS-CoV-2 positive (SARS-CoV-2⁺) cases and deaths in Sicily up to 2020, May 14th. No difference in COVID-19 prevalence was found between people with and without DM (RR 0.92 [0.79–1.09]). Case fatality was significantly higher in SARS-CoV-2⁺ with DM (RR 4.5 [3.55–5.71]). No diabetes medication was associated with differences in risk for SARS-Cov2 infection.Conclusionsin Sicily, DM was not a risk factor for COVID-19 infection, whereas it was associated with a higher case fatality.     

Laboratory Biosafety: Descriptive epidemiology of deceased cases of COVID-19 reported during the initial wave of the epidemic in Canada,January 15 to July 9, 2020

This rapid communication describes deaths among cases of coronavirus disease 2019 (COVID-19) in Canada by province and territory and by case characteristics. Of the 106,804 cases of COVID-19 reported in Canada as of July 9, 2020, 8,749 resulted in death, which represents a mortality rate of 23.3 per 100,000 population, and a case fatality rate (CFR) of 8.2%. Within Canada, the CFR ranged from 0% to 10.0% by province and territory, with the differences likely reflecting differences in the extent of the epidemic within each jurisdiction, and where and among whom localized outbreaks occurred (e.g. outbreaks in long term care homes, affecting older individuals with multi-morbidities). The CFRs increased with age and with the number of pre-existing medical conditions, and among residents of long term care and seniors’ homes. Plans are underway to collect more detailed information on cases, including race and ethnicity, which will add to our understanding of the communities most impacted by COVID-19. Studies of excess mortality, a measure of the number of people who died from any cause as compared with the historical average, will help to clarify the full impact of COVID-19 within Canadian jurisdictions.     

The Impact of COVID-19 on Mortality in Spain: Monitoring Excess Mortality (MoMo) and the Surveillance of Confirmed COVID-19 Deaths

Measuring mortality has been a challenge during the COVID-19 pandemic. Here, we compared the results from the Spanish daily mortality surveillance system (MoMo) of excess mortality estimates, using a time series analysis, with those obtained for the confirmed COVID-19 deaths reported to the National Epidemiological Surveillance Network (RENAVE). The excess mortality estimated at the beginning of March 2020 was much greater than what has been observed in previous years, and clustered in a very short time. The cumulated excess mortality increased with age. In the first epidemic wave, the excess mortality estimated by MoMo was 1.5 times higher than the confirmed COVID-19 deaths reported to RENAVE, but both estimates were similar in the following pandemic waves. Estimated excess mortality and confirmed COVID-19 mortality rates were geographically distributed in a very heterogeneous way. The greatest increase in mortality that has taken place in Spain in recent years was detected early by MoMo, coinciding with the spread of the COVID-19 pandemic. MoMo is able to identify risk situations for public health in a timely manner, relying on mortality in general as an indirect indicator of various important public health problems.     

Excess diabetes-related deaths: The role of comorbidities through different phases of the COVID-19 pandemic

Background and aimsDiabetes confers an excess risk of death to COVID-19 patients. Causes of death are now available for different phases of the pandemic, encompassing different viral variants and COVID-19 vaccination. The aims of the present study were to update multiple causes of death data on diabetes-related mortality during the pandemic and to estimate the impact of common diabetic comorbidities on excess mortality.Methods and resultsDiabetes-related deaths in 2020–2021 were compared with the 2018–2019 average; furthermore, age-standardized rates observed during the pandemic were compared with expected figures obtained from the 2008–2019 time series through generalized estimating equation models. Changes in diabetes mortality associated with specific comorbidities were also computed. Excess diabetes-related mortality was +26% in 2020 and +18% in 2021, after the initiation of the vaccination campaign. The presence of diabetes and hypertensive diseases was associated with the highest mortality increase, especially in subjects aged 40–79 years, +41% in 2020 and +30% in 2021.ConclusionThe increase in diabetes-related deaths exceeded that observed for all-cause mortality, and the risk was higher when diabetes was associated with hypertensive diseases. Notably, the excess mortality decreased in 2021, after the implementation of vaccination against COVID-19.     

Brief Report: Estimates from 31 countries show the significant impact of COVID-19 excess mortality on the incidence of family bereavement

Excess mortality associated with the COVID-19 pandemic has led many to experience the loss of family members, with significant negative outcomes. We quantify the extent to which these population-wide rates of kin loss represent a departure from levels expected in the absence of COVID-19 excess mortality and consider which demographic groups are most likely to be affected. Results for biological kin in 31 countries indicate dramatic increases in excess kin loss associated with excess mortality and follow a generational pattern consistent with COVID-19 mortality risk by age. During periods of high excess mortality, the number of younger individuals losing a grandparent increased by up to 845 per 100,000, or 1.2 times expected levels (for individuals aged 30 to 44 y in the United Kingdom in April 2020), while the number of older individuals losing a sibling increased by up to 511 per 100,000 or 1.15 times (for individuals aged 65 y and over in Poland in November 2020). Our monthly multicountry estimates of excess kin loss complement existing point estimates of the number of individuals bereaved by COVID-19 mortality [Verdery et al., Proc. Natl. Acad. Sci. U.S.A. 117, 17695–17701 (2020); Kidman et al., JAMA Pediatr. 175, 745–746 (2021); Hillis et al., Lancet 398, 391–402 (2021)] and highlight the role of heterogeneous excess mortality in shaping country experiences.     

Differential mortality in COVID-19 patients from India and western countries

Background and aimsCOVID-19 disease has been associated with disproportionate mortality amongst world population. We try to elucidate various reasons for lower mortality rate in the Indian subcontinent due to COVID-19 pandemic.MethodWe carried out a comprehensive review of the literature using suitable keywords such as ‘COVID-19’, ‘Pandemics’, ‘disease outbreaks’ and ‘India’ on the search engines of PubMed, SCOPUS, Google Scholar and Research Gate in the month of May 2020 during the current COVID-19 pandemic and assessed mortality data.ResultsThe mortality observed in Indian and south Asian subcontinent is lower than in the west.Multifactorial reasons indicated for this differential mortality due to COVID-19 have been described in the current literature.ConclusionsThe effects of COVID-19 on the health of racial and ethnic minority groups are still emerging with disproportionate burden of illness and death amongst some black and ethnic minority groups. Overall the current COVID-19 related mortality appears to be lower in the health and resource challenged populous Indian subcontinent. Further scientific studies would be helpful to understand this disparity in mortality due to COVID-19 in the world population.     

Assessing inequities underlying racial disparities of COVID-19 mortality in Louisiana parishes

High COVID-19 mortality among Black communities heightened the pandemic’s devastation. In the state of Louisiana, the racial disparity associated with COVID-19 mortality was significant; Black Americans accounted for 50% of known COVID-19–related deaths while representing only 32% of the state’s population. In this paper, we argue that structural racism resulted in a synergistic framework of cumulatively negative determinants of health that ultimately affected COVID-19 deaths in Louisiana Black communities. We identify the spatial distribution of social, environmental, and economic stressors across Louisiana parishes using hot spot analysis to develop aggregate stressors. Further, we examine the correlation between stressors, cumulative health risks, COVID-19 mortality, and the size of Black populations throughout Louisiana. We hypothesized that parishes with larger Black populations (percentages) would have larger stressor values and higher cumulative health risks as well as increased COVID-19 mortality rates. Our results suggest two categories of parishes. The first group has moderate levels of aggregate stress, high population densities, predominately Black populations, and high COVID-19 mortality. The second group of parishes has high aggregate stress, lower population densities, predominantly Black populations, and initially low COVID-19 mortality that increased over time. Our results suggest that structural racism and inequities led to severe disparities in initial COVID-19 effects among highly populated Black Louisiana communities and that as the virus moved into less densely populated Black communities, similar trends emerged.

By March 2020, the novel coronavirus (COVID-19) had spread across the United States, first affecting large population hubs and then moving into smaller rural communities. With widespread effects by April 2020, it was clear that exposure to COVID-19 infection and mortality were not equal across US populations. Communities marginalized by race/ethnicity, poverty, health care, employment, and other variables were experiencing higher infection and mortality rates (1–4). Foreseeably, social, economic, and even environmental determinants of health have played a significant role in a community’s risk to a natural disaster, and the COVID-19 pandemic seemed to be no different (5–7). We argue that the clustering of COVID-19 mortality is syndemic and arises at least partially from interactions with other infrastructure and community interactions.     

COVID-19 and mortality in doctors

Background and aimsCOVID-19 disease appear to have been associated with significant mortality amongst doctors and health care workers globally. We explore the various risk factors associated with this occupational risk, especially focusing on India. This may elucidate lessons to protect these frontline workers during the COVID-19 pandemic.MethodsWe carried out a comprehensive review of the literature using suitable keywords such as ‘COVID-19’, ‘pandemics’, ‘physicians’ ‘mortality’ and ‘health personnel’ on the search engines of PubMed, SCOPUS, Google Scholar and ResearchGate in the month of July 2020 during the current COVID-19 pandemic and assessed mortality data.ResultsMortality in health care professionals has been on the rise. The countries which faced the pandemic in the early months of 2020 have had a huge surge in mortality amongst doctors due to COVID-19. India continues to show a rising trend in COVID-19 cases, however although compared to the western world India has seen a comparatively favourable statistic. Male gender, elderly doctors and those belonging to Black, Asian, and Minority Ethnic (BAME) community seem to be predisposing factors in the western world.ConclusionCOVID-19 has been associated with an increased mortality in doctors and health care workers. Until an effective cure/vaccine is developed, risk assessments at work, mitigating confounding factors, adequate supply of personal protective equipment (PPE) and enhanced protection against infection are necessary to protect health care professionals on the coronavirus frontline. Otherwise this occupational risk can lead to further untimely mortality and become another unintended consequence of the COVID-19 pandemic.     

Long time frames to detect the impact of changing COVID-19 measures,Canada, March to July 2020

BackgroundMany countries have implemented population-wide interventions to control COVID-19, with varying extent and success. Many jurisdictions have moved to relax measures, while others have intensified efforts to reduce transmission.AimWe aimed to determine the time frame between a population-level change in COVID-19 measures and its impact on the number of cases.MethodsWe examined how long it takes for there to be a substantial difference between the number of cases that occur following a change in COVID-19 physical distancing measures and those that would have occurred at baseline. We then examined how long it takes to observe this difference, given delays and noise in reported cases. We used a susceptible-exposed-infectious-removed (SEIR)-type model and publicly available data from British Columbia, Canada, collected between March and July 2020.ResultsIt takes 10 days or more before we expect a substantial difference in the number of cases following a change in COVID-19 control measures, but 20–26 days to detect the impact of the change in reported data. The time frames are longer for smaller changes in control measures and are impacted by testing and reporting processes, with delays reaching ≥ 30 days.ConclusionThe time until a change in control measures has an observed impact is longer than the mean incubation period of COVID-19 and the commonly used 14-day time period. Policymakers and practitioners should consider this when assessing the impact of policy changes. Rapid, consistent and real-time COVID-19 surveillance is important to minimise these time frames.