Technical Report

OCLA Report 2020-1: Criticism of Government Response to COVID-19 in Canada

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We review the scientific literature about general-population-lockdown and social-distancing measures, which is relevant to mitigation policy in Canada. Federal and provincial Canadian government responses to and communications about COVID-19 have been irresponsible. The latest research implies that the government interventions to “flatten the curve” risk causing significant additional cumulative COVID-19 deaths, due to seasonal driving of transmissibility and delayed societal immunity. (OCLA Report 2020-1 - Ontario Civil Liberties Association)

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OBJECTIVE: To evaluate the relative risk of COVID-19 death in people <65 years old versus older individuals in the general population, to provide estimates of absolute risk of COVID-19 death at the population level, and to understand what proportion of COVID-19 deaths occur in non-elderly people without underlying diseases in epicenters of the pandemic. ELIGIBLE DATA: Countries and US states or major cities with at least 250 COVID-19 deaths as of 4/4/2020 and with information available on death counts according to age strata, allowing to calculate the number of deaths in people with age <65. Data were available for Belgium, Germany, Italy, Netherlands, Portugal, Spain, Sweden, and Switzerland, as well as Louisiana, Michigan, Washington states and New York City as of April 4, 2020. MAIN OUTCOME MEASURES: Proportion of COVID-19 deaths that occur in people <65 years old; relative risk of COVID-19 death in people <65 versus ≥65 years old; absolute risk of death in people <65 and in those ≥80 years old in the general population as of 4/4/2020; absolute death risk expressed as equivalent of death risk from driving a motor vehicle. RESULTS: Individuals with age <65 account for 5%-9% of all COVID-19 deaths in the 8 European epicenters, and approach 30% in three US hotbed locations. People <65 years old had 34- to 73-fold lower risk than those ≥65 years old in the European countries and 13- to 15-fold lower risk in New York City, Louisiana and Michigan. The absolute risk of COVID-19 death ranged from 1.7 per million for people <65 years old in Germany to 79 per million in New York City. The absolute risk of COVID-19 death for people ≥80 years old ranged from approximately 1 in 6,000 in Germany to 1 in 420 in Spain. The COVID-19 death risk in people <65 years old during the period of fatalities from the epidemic was equivalent to the death risk from driving between 9 miles per day (Germany) and 415 miles per day (New York City). People <65 years old and not having any underlying predisposing conditions accounted for only 0.3%, 0.7%, and 1.8% of all COVID-19 deaths in Netherlands, Italy, and New York City. CONCLUSIONS: People <65 years old have very small risks of COVID-19 death even in the hotbeds of the pandemic and deaths for people <65 years without underlying predisposing conditions are remarkably uncommon. Strategies focusing specifically on protecting high-risk elderly individuals should be considered in managing the pandemic.
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Detection of SARS-CoV-2 infections to date has relied on RT-PCR testing. However, a failure to identify early cases imported to a country, bottlenecks in RT-PCR testing, and the existence of infections which are asymptomatic, sub-clinical, or with an alternative presentation than the standard cough and fever have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how publicly available CDC influenza-like illness (ILI) outpatient surveillance data can be repurposed to estimate the detection rate of symptomatic SARS-CoV-2 infections. We find a surge of non-influenza ILI above the seasonal average and show that this surge is correlated with COVID case counts across states. By quantifying the number of excess ILI patients in March relative to previous years and comparing excess ILI to confirmed COVID case counts, we estimate the symptomatic case detection rate of SARS-CoV-2 in the US to be 1/100 to 1/1000. This corresponds to approximately 10 million presumed symptomatic SARS-CoV-2 patients across the US during the week starting on March 15, 2020. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to be doubling slower than every three days. Together these results suggest a conceptual model for the COVID epidemic in the US in which rapid spread across the US are combined with a large population of infected patients with presumably mild-to-moderate clinical symptoms. We emphasize the importance of testing these findings with seroprevalence data, and discuss the broader potential to repurpose outpatient time series for early detection and understanding of emerging infectious diseases.
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About one month after the COVID-19 epidemic peaked in Mainland China and SARS-CoV-2 migrated to Europe and then the U.S., the epidemiological data begin to provide important insights into the risks associated with the disease and the effectiveness of intervention strategies such as travel restrictions and lockdowns (“social distancing”). Respiratory diseases, including the 2003 SARS epidemic, remain only about two months in any given population, although peak incidence and lethality can vary. The epidemiological data suggest that at least two strains of the 2020 SARS-CoV-2 virus have evolved during its migration from Mainland China to Europe. South Korea, Iran, Italy, and Italy’s neighbors were hit by the more dangerous “SKII” variant. While the epidemic in continental Asia is about to end, and in Europe about to level off, the more recent epidemic in the younger US population is still increasing, albeit not exponentially anymore. The peak level will likely depend on which of the strains has entered the U.S. first. The same models that help us to understand the epidemic also help us to choose prevention strategies. Containment of high-risk people, like the elderly, and reducing disease severity, either by vaccination or by early treatment of complications, is the best strategy against a respiratory virus disease. Lockdowns can be effective during the month following the peak incidence in infections, when the exponential increase of cases ends. Earlier containment of low-risk people merely prolongs the time the virus needs to circulate until the incidence is high enough to initiate “herd immunity”. Later containment is not helpful, unless to prevent a rebound if containment started too early. About the Author Dr. Wittkowski received his PhD in computer science from the University of Stuttgart and his ScD (Habilitation) in Medical Biometry from the Eberhard-Karls-University Tübingen, both Germany. He worked for 15 years with Klaus Dietz, a leading epidemiologist who coined the term “reproduction number”, on the Epidemiology of HIV before heading for 20 years the Department of Biostatistics, Epidemiology, and Research Design at The Rockefeller University, New York. Dr. Wittkowski is currently the CEO of ASDERA LLC, a company discovering novel interventions against complex (incl. coronavirus) diseases from data of genome-wide association studies.
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The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of "winning" depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one dominant high-status individual and all other individuals having zero status. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a dominant class. We compare our model predictions to human societies using household income as a proxy for societal status and find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status "tail". We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.
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Author Summary The origin of seasonality in influenza transmission is both of palpable public health importance and basic scientific interest. Here, we present statistical analyses and a mathematical model of epidemic influenza transmission that provide strong epidemiological evidence for the hypothesis that absolute humidity (AH) drives seasonal variations of influenza transmission in temperate regions. We show that the onset of individual wintertime influenza epidemics is associated with anomalously low AH conditions throughout the United States. In addition, we use AH to modulate the basic reproductive number of influenza within a mathematical model of influenza transmission and compare these simulations with observed excess pneumonia and influenza mortality. These simulations capture key details of the observed seasonal cycle of influenza throughout the US. The results indicate that AH affects both the seasonality of influenza incidence and the timing of individual wintertime influenza outbreaks in temperate regions. The association of anomalously low AH conditions with the onset of wintertime influenza outbreaks suggests that skillful, short-term probabilistic forecasts of epidemic influenza could be developed.
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Severe acute respiratory syndrome (SARS) caused by a newly identified coronavirus (SARS-CoV) is a serious emerging human infectious disease. In this report, we immunized ferrets (Mustela putorius furo) with recombinant modified vaccinia virus Ankara (rMVA) expressing the SARS-CoV spike (S) protein. Immunized ferrets developed a more rapid and vigorous neutralizing antibody response than control animals after challenge with SARS-CoV; however, they also exhibited strong inflammatory responses in liver tissue. Inflammation in control animals exposed to SARS-CoV was relatively mild. Thus, our data suggest that vaccination with rMVA expressing SARS-CoV S protein is associated with enhanced hepatitis.
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Development of strategies for mitigating the severity of a new influenza pandemic is now a top global public health priority. Influenza prevention and containment strategies can be considered under the broad categories of antiviral, vaccine and non-pharmaceutical (case isolation, household quarantine, school or workplace closure, restrictions on travel) measures. Mathematical models are powerful tools for exploring this complex landscape of intervention strategies and quantifying the potential costs and benefits of different options. Here we use a large-scale epidemic simulation to examine intervention options should initial containment of a novel influenza outbreak fail, using Great Britain and the United States as examples. We find that border restrictions and/or internal travel restrictions are unlikely to delay spread by more than 2-3 weeks unless more than 99% effective. School closure during the peak of a pandemic can reduce peak attack rates by up to 40%, but has little impact on overall attack rates, whereas case isolation or household quarantine could have a significant impact, if feasible. Treatment of clinical cases can reduce transmission, but only if antivirals are given within a day of symptoms starting. Given enough drugs for 50% of the population, household-based prophylaxis coupled with reactive school closure could reduce clinical attack rates by 40-50%. More widespread prophylaxis would be even more logistically challenging but might reduce attack rates by over 75%. Vaccine stockpiled in advance of a pandemic could significantly reduce attack rates even if of low efficacy. Estimates of policy effectiveness will change if the characteristics of a future pandemic strain differ substantially from those seen in past pandemics.
Background: Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions. Methods: We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23-24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI). Findings: In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47-2·86) and that 75 815 individuals (95% CrI 37 304-130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8-7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227-805), 113 (57-193), 98 (49-168), 111 (56-191), and 80 (40-139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1-2 weeks. Interpretation: Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally. Funding: Health and Medical Research Fund (Hong Kong, China).
BACKGROUND: Travel restrictions were implementeded on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New 'big data' approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures. METHODS: We analysed anonymous mobile phone call detail records (CDRs) from a leading operator in Sierra Leone between 20 March and 1 July in 2015. We used an anomaly detection algorithm to assess changes in travel during a national 'stay at home' lockdown from 27 to 29 March. To measure the magnitude of these changes and to assess effect modification by region and historical Ebola burden, we performed a time series analysis and a crossover analysis. RESULTS: Routinely collected mobile phone data revealed a dramatic reduction in human mobility during a 3-day lockdown in Sierra Leone. The number of individuals relocating between chiefdoms decreased by 31% within 15 km, by 46% for 15-30 km and by 76% for distances greater than 30 km. This effect was highly heterogeneous in space, with higher impact in regions with higher Ebola incidence. Travel quickly returned to normal patterns after the restrictions were lifted. CONCLUSIONS: The effects of travel restrictions on mobility can be large, targeted and measurable in near real-time. With appropriate anonymization protocols, mobile phone data should play a central role in guiding and monitoring interventions for epidemic containment.
Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013–2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.
In Hong Kong, kindergartens and primary schools were closed when local transmission of pandemic (H1N1) 2009 was identified. Secondary schools closed for summer vacation shortly afterwards. By fitting a model of reporting and transmission to case data, we estimated that transmission was reduced approximately 25% when secondary schools closed.
In response to WHO raising the influenza pandemic alert level from phase five to phase six, health officials around the world are carefully reviewing pandemic mitigation protocols. School closure (also called class dismissal in North America) is a non-pharmaceutical intervention that is commonly suggested for mitigating influenza pandemics. Health officials taking the decision to close schools must weigh the potential health benefits of reducing transmission and thus case numbers against high economic and social costs, difficult ethical issues, and the possible disruption of key services such as health care. Also, if schools are expected to close as a deliberate policy option, or just because of high levels of staff absenteeism, it is important to plan to mitigate the negative features of closure. In this context, there is still debate about if, when, and how school closure policy should be used. In this Review, we take a multidisciplinary and holistic perspective and review the multiple aspects of school closure as a public health policy. Implications for the mitigation of the swine-origin influenza A H1N1 pandemic are also discussed.
The rapid containment of the Singapore severe acute respiratory syndrome (SARS) outbreak in 2003 involved the introduction of several stringent control measures. These measures had a profound impact on the healthcare system and community, and were associated with significant disruptions to normal life, business and social intercourse. An assessment of the relative effectiveness of the various control measures is critical in preparing for future outbreaks of a similar nature. The very "wide-net" surveillance, isolation and quarantine policy adopted was effective in ensuring progressively earlier isolation of probable SARS cases. However, it resulted in nearly 8000 contacts being put on home quarantine and 4300 on telephone surveillance, with 58 individuals eventually being diagnosed with probable SARS. A key challenge is to develop very rapid and highly sensitive tests for SARS infection, which would substantially reduce the numbers of individuals that need to be quarantined without decreasing the effectiveness of the measure. Daily temperature monitoring of all healthcare workers (HCWs) in hospitals was useful for early identification of HCWs with SARS. However, daily temperature screening of children in schools failed to pick up any SARS cases. Similarly, temperature screening at the airport and other points of entry did not yield any SARS cases. Nevertheless, the latter 2 measures probably helped to reassure the public that schools and the community were safe during the SARS outbreak. Strong political leadership and effective command, control and coordination of responses were critical factors for the containment of the outbreak.
How will country-based mitigation measures influence the course of the COVID-19 epidemic?
Anderson et al. (2020) "How will country-based mitigation measures influence the course of the COVID-19 epidemic?", The Lancet, Comment| Volume 395, ISSUE 10228, P931-934, March 21, 2020.
Coronavirus vaccines: five key questions as trials begin -Some experts warn that accelerated testing will involve some risky trade-offs
  • Callaway
Callaway (2020) "Coronavirus vaccines: five key questions as trials begin -Some experts warn that accelerated testing will involve some risky trade-offs", Nature, vol. 579, p. 481, doi: 10.1038/d41586-020-00798-8
Estimates of global seasonal influenza-associated respiratory mortality: a modelling study
  • Iuliano
Iuliano et al. (2018) "Estimates of global seasonal influenza-associated respiratory mortality: a modelling study", Lancet, March 31; 391(10127): 1285-1300. doi: 10.1016/S0140-6736(17)33293-2.
Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
  • Kissler
Kissler et al. (2020) "Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period", Science, Published Online 14 Apr 2020, DOI: 10.1126/science.abb5793
Impact of Influenza Epidemics on Mortality in the United States from
  • Kendal Lui
Lui and Kendal (1987) "Impact of Influenza Epidemics on Mortality in the United States from October 1972 to May 1985", Am J Public Health, 77:712-716.
Characteristics of COVID-19 patients dying in Italy
  • Palmieri
Palmieri et al. (2020) "Characteristics of COVID-19 patients dying in Italy -Report based on available data on March 20th, 2020", COVID-19 Surveillance Group
A composite epidemic curve for seasonal influenza in Canada with an international comparison
  • Schanzer
Schanzer et al. (2010) "A composite epidemic curve for seasonal influenza in Canada with an international comparison", Influenza Other Respir Viruses, 4(5):295-306. doi:10.1111/j.1750-2659.2010.00154.x
Social distancing and mobility reductions have reduced COVID-19 transmission in King County, WA
  • Thakkar
Thakkar et al. (2020) "Social distancing and mobility reductions have reduced COVID-19 transmission in King County, WA", Institute for Disease Modeling pdf Verity et al. (2020) "Estimates of the severity of coronavirus disease 2019: a model-based analysis", The Lancet, Published Online 30 March 2020,