Infection fatality rate of COVID-19 inferred from seroprevalence data

Impact of cross-reactivity and herd immunity on SARS-CoV-2 pandemic severity

Public health systems reported low mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in East Asia, in low-income countries, and for children during the first year of the SARS-CoV-2 pandemic. These reports led commentators to suggest that cross-reactive immunity from prior exposure to other pathogens reduced fatality risk. Resolution of initial infection waves also contributed to speculation that herd immunity prevented further waves prior to vaccination. Serology instead implied that immunity was too limited to achieve herd immunity and that there was little impact from cross-reactive protection. Paediatric deaths exceeded those from influenza, with higher age-specific fatality risk in lower-income nations and similar fatality risk in East Asia compared with demographically similar regions. Neither pre-outbreak exposure to related pathogens nor immunity induced by initial infection waves are necessarily a reliable response to future pathogen outbreaks. Preparedness for future pathogen outbreaks should instead focus on strategies such as voluntary behavioural changes, nonpharmaceutical interventions, and vaccination.

Postmarketing studies: can they provide a safety net for COVID-19 vaccines in the UK?

In the current era of the COVID-19 pandemic, the world has never been more interested in the process of vaccine development. While researchers across the globe race to find an effective yet safe vaccine to protect populations from the newly emergent SARS-CoV-2 virus, more than one-third of the world has been subjected to either full or partial lockdown measures. With communities having felt the burden of prolonged isolation, finding a safe and efficacious vaccine will yield direct beneficial effects on protecting against COVID-19 morbidity and mortality and help relieve the psychological and economic load on communities living with COVID-19. There is hope that with the extraordinary efforts of scientists a vaccine will become available. However, given the global public health crisis, development of a COVID-19 vaccine will need to be fast tracked through the usual prelicensing development stages and introduced with limited clinical trial data compared with those vaccines that are developed conventionally over more than a decade. In this scenario, surveillance of the vaccine in the real world becomes even more paramount. This responsibility falls to observational researchers who can provide an essential safety net by continuing to monitor the effectiveness and safety of a COVID-19 vaccine after licensing. Postauthorisation observational studies for safety and effectiveness are complementary to prelaunch clinical trials and not a replacement. In this paper, we highlight the importance of postmarketing studies for future newly licensed COVID-19 vaccines and the key epidemiological considerations.

Optimal strategies to screen health care workers for COVID-19 in the US: a cost-effectiveness analysis

Background

Transmission of SARS-CoV-2 in health care facilities poses a challenge against pandemic control. Health care workers (HCWs) have frequent and high-risk interactions with COVID-19 patients. We undertook a cost-effectiveness analysis to determine optimal testing strategies for screening HCWs to inform strategic decision-making in health care settings.

Methods

We modeled the number of new infections, quality-adjusted life years lost, and net costs related to six testing strategies including no test. We applied our model to four strata of HCWs, defined by the presence and timing of symptoms. We conducted sensitivity analyses to account for uncertainty in inputs.

Results

When screening recently symptomatic HCWs, conducting only a PCR test is preferable; it saves costs and improves health outcomes in the first week post-symptom onset, and costs $83,000 per quality-adjusted life year gained in the second week post-symptom onset. When screening HCWs in the late clinical disease stage, none of the testing approaches is cost-effective and thus no testing is preferable, yielding $11 and 0.003 new infections per 10 HCWs. For screening asymptomatic HCWs, antigen testing is preferable to PCR testing due to its lower cost.

Conclusions

Both PCR and antigen testing are beneficial strategies to identify infected HCWs and reduce transmission of SARS-CoV-2 in health care settings. IgG tests’ value depends on test timing and immunity characteristics, however it is not cost-effective in a low prevalence setting. As the context of the pandemic evolves, our study provides insight to health-care decision makers to keep the health care workforce safe and transmissions low.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12962-021-00336-x.

Representative estimates of COVID-19 infection fatality rates from four locations in India: cross-sectional study

OBJECTIVES

To estimate age-specific and sex-specific mortality risk among all SARS-CoV-2 infections in four settings in India, a major lower-middle-income country and to compare age trends in mortality with similar estimates in high-income countries.

DESIGN

Cross-sectional study.

SETTING

India, multiple regions representing combined population >150 million.

PARTICIPANTS

Aggregate infection counts were drawn from four large population-representative prevalence/seroprevalence surveys. Data on corresponding number of deaths were drawn from official government reports of confirmed SARS-CoV-2 deaths.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was age-specific and sex-specific infection fatality rate (IFR), estimated as the number of confirmed deaths per infection. The secondary outcome was the slope of the IFR-by-age function, representing increased risk associated with age.

RESULTS

Among males aged 50-89, measured IFR was 0.12% in Karnataka (95% CI 0.09% to 0.15%), 0.42% in Tamil Nadu (95% CI 0.39% to 0.45%), 0.53% in Mumbai (95% CI 0.52% to 0.54%) and an imprecise 5.64% (95% CI 0% to 11.16%) among migrants returning to Bihar. Estimated IFR was approximately twice as high for males as for females, heterogeneous across contexts and rose less dramatically at older ages compared with similar studies in high-income countries.

CONCLUSIONS

Estimated age-specific IFRs during the first wave varied substantially across India. While estimated IFRs in Mumbai, Karnataka and Tamil Nadu were considerably lower than comparable estimates from high-income countries, adjustment for under-reporting based on crude estimates of excess mortality puts them almost exactly equal with higher-income country benchmarks. In a marginalised migrant population, estimated IFRs were much higher than in other contexts around the world. Estimated IFRs suggest that the elderly in India are at an advantage relative to peers in high-income countries. Our findings suggest that the standard estimation approach may substantially underestimate IFR in low-income settings due to under-reporting of COVID-19 deaths, and that COVID-19 IFRs may be similar in low-income and high-income settings.

Preliminary Results from the FOGSI's National Registry on Pregnancy with COVID-19

Background/purpose of the study

The obstetric population is believed to be more susceptible to adverse consequences of coronavirus disease COVID-19 as compared to the general populace. Clinical characteristics and outcomes data related to COVID-19 infection in obstetric cases are limited and evolving. Most importantly, studies reporting Indian data are strikingly few and of single centre. The objective of our study was thus to address these lacunae using data registered in the FOGSI’s National registry on COVID-19 infection in pregnancy (FOGSI COVID registry).

Methods

We conducted an observational study using data retrieved from the FOGSI COVID registry. Fifty-three hospital departments participating in the registry populated data related to laboratory confirmed and hospitalized COVID-19 obstetric patients. Data for the period of 28 April 2020 to 28 August 2020 were extracted from the registry. A subset of the data was formatted, curated, standardized and harmonized. Descriptive analysis was carried out, and results reported.

Results

Of the 989 cases analyzed, 956 women were pregnant and 33 women were in the postpartum period. A total of 569 women (61.71%, n = 922) were multi-gravida, and 713 women (72.98%, n = 977) belonged to the 21–30 years age group. A total of 492 cases (52.73%, n = 966) had a gestational age > 37 weeks. A total of 754 women (83.41%, n = 904) were asymptomatic, and 32 cases (3.54%, n = 904) had severe acute respiratory infection (SARI). Fifty-six women (7.19%, n = 779) required critical care and ten women (1.01%, n = 989) died. A total of 771 pregnant women (97.23%, n = 793) gave birth of which 455 cases (59.01%) underwent a lower segment caesarean section (LSCS). There were 749 cases (95.17%, n = 771) of live birth that included eight cases of twin deliveries. 195 infants (28.34%, n = 688) were admitted to the NICU, and 13 infants (2.99%, n = 435) tested COVID-19 positive in the neonatal period. Twelve infants (1.54%, n = 779) died.

Conclusion

83.41% pregnant women were asymptomatic. COVID-19 infection in obstetric cases from India led to 59.01% LSCS procedures which are lower than many other countries. COVID-19 infection led to a higher maternal mortality and IUFD rate as compared to pregnant women that did not have COVID-19 infection in India. Vertical transmission rate is 2.99% and at par with other countries.

Oxygen and Mortality in COVID-19 Pneumonia: A Comparative Analysis of Supplemental Oxygen Policies and Health Outcomes Across 26 Countries

Introduction: Hypoxia is the main cause of morbidity and mortality in COVID-19. During the COVID-19 pandemic, some countries have reduced access to supplemental oxygen, whereas other nations have maintained and even improved access to supplemental oxygen. We examined whether variation in the nationally determined oxygen guidelines had any association with national mortality rates in COVID-19.

Methods: Three independent investigators searched for, identified, and extracted the nationally recommended target oxygen levels for the commencement of oxygen in COVID-19 pneumonia from the 29 worst affected countries. Mortality estimates were calculated from three independent sources. We then applied both parametric (Pearson's R) and non-parametric (Kendall's Tau B) tests of bivariate association to determine the relationship between case fatality rate (CFR) and target SpO₂, and also between potential confounders and CFR.

Results: Of the 26 nations included, 15 had employed conservative oxygen strategies to manage COVID-19 pneumonia. Of them, Belgium, France, USA, Canada, China, Germany, Mexico, Spain, Sweden, and the UK guidelines advised commencing oxygen when oxygen saturations (SpO₂) fell to 91% or less. A statistically significant correlation was found between SpO₂ and CFR both parametrically (R = −0.53, P < 0.01) and non-parametrically (−0.474, P < 0.01).

Conclusion: Our study highlights the disparity in oxygen provision for COVID-19 patients between the nations analysed. In those nations that pursued a conservative oxygen strategy, there was an association with higher national mortality rates. We discuss the potential reasons for such an association.

Epidemiología, clínica y distribución temporal de los casos confirmados y sospechosos de enfermedad por coronavirus (COVID-19) atendidos por un centro de salud urbano (Cáceres)

Objetivo

Describir la experiencia de la atención sanitaria a pacientes con sospecha de COVID-19 en un centro de salud tipo durante el periodo de alarma.

Diseño

Estudio observacional retrospectivo.

Emplazamiento

Centro de salud Zona Centro de Cáceres.

Participantes

Pacientes consecutivos atendidos por sospecha de infección por SARS-CoV-2 del 2 de marzo al 21 de junio de 2020.

Mediciones principales

Edad, sexo, síntomas más frecuentes atribuidos a la infección, duración de los síntomas, días hasta el alta epidemiológica, comorbilidades, tratamientos farmacológicos, método diagnóstico, derivaciones a urgencias hospitalarias, hospitalizados, afectados de neumonía, fallecidos, incapacidad temporal laboral, ámbito de diagnóstico y fase del periodo de alarma.

Resultados

Se incluyeron 464 pacientes; 53 fueron confirmados por PCR y 90 por serología. El 81,1% de los diagnósticos por PCR se produjo en las 4 primeras semanas del periodo de confinamiento. Se derivaron 29 pacientes al hospital (6,2%). Fallecieron 7 (tasa 0,52/1.000). Los síntomas predominantes en los sospechosos fueron tos, fiebre, astenia y síntomas digestivos; en los confirmados tos, disnea y fiebre. La enfermedad cardiovascular y la enfermedad renal crónica fueron más frecuentes en este último grupo (p < 0,001).

Conclusiones

La mortalidad fue similar a la española. Las variables epidemiológicas y clínicas se corresponden con las descritas en otros ámbitos. Los diagnosticados por PCR se concentraron en la primera mitad del periodo de confinamiento.

Repurposed Antiviral Drugs for the Treatment of COVID-19: Syntheses, Mechanism of Infection and Clinical Trials

COVID-19 is a public health emergency of international concern. Although considerable knowledge has been acquired with time about the viral mechanism of infection and mode of replication, yet no specific drugs or vaccines have been discovered against SARS-CoV-2 to date. There are few small molecule antiviral drugs like Remdesivir and Favipiravir, which have shown promising results in different advanced stages of clinical trials. Chloroquinine, Hydroxychloroquine, and Lopinavir- Ritonavir combination, although initially were hypothesized to be effective against SARSCoV- 2, are now discontinued from the solidarity clinical trials. This review provides a brief description of their chemical syntheses along with their mode of action, and clinical trial results available on Google and in different peer-reviewed journals till 24th October 2020.

Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany

BACKGROUND

The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals - not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted.

METHODS

Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections.

RESULTS

Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave.

CONCLUSIONS

The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus.

Prevalence of SARS-CoV-2 antibodies in France: results from nationwide serological surveillance

Assessment of the cumulative incidence of SARS-CoV-2 infections is critical for monitoring the course and extent of the COVID-19 epidemic. Here, we report estimated seroprevalence in the French population and the proportion of infected individuals who developed neutralising antibodies at three points throughout the first epidemic wave. Testing 11,000 residual specimens for anti-SARS-CoV-2 IgG and neutralising antibodies, we find nationwide seroprevalence of 0.41% (95% CI: 0.05-0.88) mid-March, 4.14% (95% CI: 3.31-4.99) mid-April and 4.93% (95% CI: 4.02-5.89) mid-May 2020. Approximately 70% of seropositive individuals have detectable neutralising antibodies. Infection fatality rate is 0.84% (95% CI: 0.70-1.03) and increases exponentially with age. These results confirm that the nationwide lockdown substantially curbed transmission and that the vast majority of the French population remained susceptible to SARS-CoV-2 in May 2020. Our study shows the progression of the first epidemic wave and provides a framework to inform the ongoing public health response as viral transmission continues globally.

Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates

Susceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15-June 30, 2020, we estimate the underreporting factor for cases at 34-53 (deaths: 8-13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27-July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30-42 for cases. Together, these imply approximately 96-98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13-22 (deaths: 3-7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15-23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17-21. Together, these updated estimates imply approximately 92-96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.

Using excess deaths and testing statistics to determine COVID-19 mortalities

Factors such as varied definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US from January 2020 until February 2021 is 9[Formula: see text] higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find statistically insignificant or even negative excess deaths for at least most of 2020 in places such as Germany, Denmark, and Norway.

The road from evidence to policies and the erosion of the standards of democratic scrutiny in the COVID-19 pandemic

The COVID-19 pandemic poses extraordinary public health challenges. In order to respond to such challenges, most democracies have relied on so-called 'evidence-based' policies, which supposedly devolve to science the burden of their justification. However, the biomedical sciences can only provide a theory-laden evidential basis, while reliable statistical data for policy support is often scarce. Therefore, scientific evidence alone cannot legitimise COVID-19 public health policies, which are ultimately based on political decisions. Given this inevitable input on policy-making, the risk of arbitrariness is ubiquitous and democratic scrutiny becomes essential to counter it. During the COVID-19 pandemic, the standards of scientific and democratic scrutiny have been, as a matter of fact, substantially lowered. This erosion potentially damages democracy.

Seroprevalence of SARS-CoV-2 in Bhubaneswar, India: findings from three rounds of community surveys

The study aims to estimate and compare the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence, the fraction of asymptomatic or subclinical infections in the population, determine the demographic risk factors and analyse the antibody development at different time points among adults in Bhubaneswar city, India. This was a serial three-round cross-sectional, community-based study where participants were selected from the residents of Bhubaneswar city using multi-stage random sampling. Blood samples were collected during household visits along with demographic and clinical data from every participant. Total anti-SARS-CoV-2 antibody present in serum was assessed using the electro-chemiluminescence immunoassay platform. Temporal comparisons of the community seroprevalence were performed against the detected number of cumulative cases, active cases, recoveries and deaths. A total of 3693 participants were enrolled in this study with a cumulative non-response rate of 18.33% in all the three rounds. The gender-weighted seroprevalence for the city in the first round was 1.55% (95% confidence interval (CI) 0.84-2.58), second round was 5.27% (95% CI 4.13-6.59) and in the third round was 49.04% (95% CI 46.39-51.68). In the first round, the seroprevalence was found to be highest in the elderly population, whereas the seroprevalence for the second and third phases was highest in the age group of 30-39 years. Seroprevalence showed an increasing trend over the three time periods, with the highest seropositivity rates among individuals sampled between 16 and 18 September 2020. By the third round, 93.93% of those who had previously been tested positive by real-time reverse transcription polymerase chain reaction had seroconversion and 46.57% of those who had been tested negative also showed seroconversion. Infection to case ratio during first round was 27.05, for second round and third round it was 5.62 and 17.91, respectively.

[SARS-CoV‑2 incidental findings among Hamburg deaths: an epidemiological monitoring during the dynamic infection event in spring 2020]

Background

In the context of the COVID-19-pandemic, mortality and incidence are key determinants to assess the transmission dynamics and the resulting potential threat. Systematic microbiological monitoring of deaths provides a fundamental basis to particularly assess underrecording of community-acquired mortality. It should be further elucidated whether a death cohort of previously unreported cases may be structurally different from the cohort of officially registered cases.

Methods

A systematic reverse transcription (RT) qPCR testing for SARS-CoV‑2 infections from nasopharyngeal swab samples was carried out. A representative sample of corpses from crematoria and the Institute of Legal Medicine of the Federal State of Hamburg were included. A comparative analysis of primarily reported and unreported fatalities in an 8‑week period after occurrence of the first pandemic-related deaths in Hamburg was performed.

Results

A total of 1231 deaths were included, all of which were previously unsuspicious for SARS-CoV‑2 infection. Thereof 29 cases of previously unknown infections were recorded. In the first phase of the pandemic, incidental findings predominantly occurred among younger people from domestic environments with unclear or unnatural manner of death at the Institute of Legal Medicine. Over time, incidental findings investigated at the crematoria increased, mostly related to nursing home residents. The overall cohort showed no significant sociodemographic differences to a comparative collective of known SARS-CoV‑2-associated deaths. Primarily unreported cases showed a significantly lower proportion of COVID-19 as the underlying cause of death.

Conclusion

A systematic PCR-based monitoring of deaths allows a more targeted detection and classification of SARS-CoV‑2 positive cases. A preventive contribution can be made by disclosing unreported pandemic-related cases of death.

Is a Mask That Covers the Mouth and Nose Free from Undesirable Side Effects in Everyday Use and Free of Potential Hazards?

Many countries introduced the requirement to wear masks in public spaces for containing SARS-CoV-2 making it commonplace in 2020. Up until now, there has been no comprehensive investigation as to the adverse health effects masks can cause. The aim was to find, test, evaluate and compile scientifically proven related side effects of wearing masks. For a quantitative evaluation, 44 mostly experimental studies were referenced, and for a substantive evaluation, 65 publications were found. The literature revealed relevant adverse effects of masks in numerous disciplines. In this paper, we refer to the psychological and physical deterioration as well as multiple symptoms described because of their consistent, recurrent and uniform presentation from different disciplines as a Mask-Induced Exhaustion Syndrome (MIES). We objectified evaluation evidenced changes in respiratory physiology of mask wearers with significant correlation of O2 drop and fatigue (p < 0.05), a clustered co-occurrence of respiratory impairment and O2 drop (67%), N95 mask and CO2 rise (82%), N95 mask and O2 drop (72%), N95 mask and headache (60%), respiratory impairment and temperature rise (88%), but also temperature rise and moisture (100%) under the masks. Extended mask-wearing by the general population could lead to relevant effects and consequences in many medical fields.

COVID-19 PREDICTION IN SOUTH AFRICA: ESTIMATING THE UNASCERTAINED CASES- THE HIDDEN PART OF THE EPIDEMIOLOGICAL ICEBERG

Understanding the impact of non-pharmaceutical interventions as well as accounting for the unascertained cases remain critical challenges for epidemiological models for understanding the transmission dynamics of COVID-19 spread. In this paper, we propose a new epidemiological model (eSEIRD) that extends the widely used epidemiological models such as extended Susceptible-Infected-Removed model (eSIR) and SAPHIRE (initially developed and used for analyzing data from Wuhan). We fit these models to the daily ascertained infected (and removed) cases from March 15, 2020 to Dec 31, 2020 in South Africa that reported the largest number of confirmed COVID-19 cases and deaths from the WHO African region. Using the eSEIRD model, the COVID-19 transmission dynamics in South Africa was characterized by the estimated basic reproduction number (R 0) starting at 3.22 (95%CrI: [3.19, 3.23]) then dropping below 2 following a mandatory lockdown implementation and subsequently increasing to 3.27 (95%CrI: [3.27, 3.27]) by the end of 2020. The initial decrease of effective reproduction number followed by an increase suggest the effectiveness of early interventions and the combined effect of relaxing strict interventions and emergence of a new coronavirus variant in South Africa. The low estimated ascertainment rate was found to vary from 1.65% to 9.17% across models and time periods. The overall infection fatality ratio (IFR) was estimated as 0.06% (95%CrI: [0.04%, 0.22%]) accounting for unascertained cases and deaths while the reported case fatality ratio was 2.88% (95% CrI: [2.45%, 6.01%]). The models predict that from December 31, 2020, to April 1, 2021, the predicted cumulative number of infected would reach roughly 70% of total population in South Africa. Besides providing insights on the COVID-19 dynamics in South Africa, we develop powerful forecasting tools that enable estimation of ascertainment rates and IFR while quantifying the effect of intervention measures on COVID-19 spread.

Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5-12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22-1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

Lockdowns and the COVID-19 pandemic: What is the endgame?

An overall long-term strategy for managing the coronavirus disease 2019 (COVID-19) pandemic is presented. This strategy will need to be maintained until herd immunity is achieved, hopefully through vaccination rather than natural infection. We suggest that a pure test-trace-isolate strategy is likely not practicable in most countries, and a degree of social distancing, ranging up to full lockdown, is the main public-health tool to mitigate the COVID-19 pandemic. Guided by reliable surveillance data, distancing should be continuously optimised down to the lowest sustainable level that guarantees a low and stable infection rate in order to balance its wide-ranging negative effects on public health. The qualitative mixture of social-distancing measures also needs to be carefully optimised in order to minimise social costs.

Rapid review of COVID-19 epidemic estimation studies for Iran

BACKGROUND

To inform researchers about the methodology and results of epidemic estimation studies performed for COVID-19 epidemic in Iran, we aimed to perform a rapid review.

METHODS

We searched for and included published articles, preprint manuscripts and reports that estimated numbers of cumulative or daily deaths or cases of COVID-19 in Iran. We found 131 studies and included 29 of them.

RESULTS

The included studies provided outputs for a total of 84 study-model/scenario combinations. Sixteen studies used 3-4 compartmental disease models. At the end of month two of the epidemic (2020-04-19), the lowest (and highest) values of predictions were 1,777 (388,951) for cumulative deaths, 20,588 (2,310,161) for cumulative cases, and at the end of month four (2020-06-20), were 3,590 (1,819,392) for cumulative deaths, and 144,305 (4,266,964) for cumulative cases. Highest estimates of cumulative deaths (and cases) for latest date available in 2020 were 418,834 on 2020-12-19 (and 41,475,792 on 2020-12-31). Model estimates predict an ominous course of epidemic progress in Iran. Increase in percent population using masks from the current situation to 95% might prevent 26,790 additional deaths (95% confidence interval 19,925-35,208) by the end of year 2020.

CONCLUSIONS

Meticulousness and degree of details reported for disease modeling and statistical methods used in the included studies varied widely. Greater heterogeneity was observed regarding the results of predicted outcomes. Consideration of minimum and preferred reporting items in epidemic estimation studies might better inform future revisions of the available models and new models to be developed. Not accounting for under-reporting drives the models' results misleading.

The Burden of Malnutrition and Fatal COVID-19: A Global Burden of Disease Analysis

Background: Although reasonable to assume, it is not yet clear whether malnourished countries are at higher risk for severe or fatal coronavirus disease 2019 (COVID-19). This study aims to identify the countries where prevalent malnutrition may be a driving factor for fatal disease after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods: Using estimates from the Global Burden of Disease 2019, country-level burden of malnutrition was quantified using four indicators: death rates for child growth failure (underweight, stunting, and/or wasting) and years lived with disability (YLD) attributed to iron and vitamin A deficiencies and high body mass index (BMI). Global mortality descriptors of the ongoing COVID-19 pandemic were extracted from the European Centre for Disease Prevention and Control, and case fatality ratios (CFRs) were calculated introducing a lag time of 10 weeks after the first death of a confirmed case. Bivariate analyses for 172 countries were carried out for malnutrition indicators and fatal COVID-19. Correlations between burden indicators were characterized by Spearman's rank correlation coefficients (ρ) and visually by scatterplots. Restricted cubic splines and underlying negative binomial regressions adjusted for countries' age-structure, prevalent chronic comorbidities related to COVID-19, population density, and income group were used to explore non-linear relationships. Results: Stratified by the World Bank income group, a moderate positive association between YLD rates for iron deficiency and CFRs for COVID-19 was observed for low-income countries (ρ = 0.60, p = 0.027), whereas no clear indications for the association with child growth failure, vitamin A deficiency, or high BMI were found (ρ < 0.30). Countries ranking high on at least three malnutrition indicators and presenting also an elevated CFR for COVID-19 are sub-Saharan African countries, namely, Angola, Burkina Faso, Chad, Liberia, Mali, Niger, Sudan, and Tanzania, as well as Yemen and Guyana. Conclusions: Population-level malnutrition appears to be related to increased rates of fatal COVID-19 in areas with an elevated burden of undernutrition, such as countries in the Sahel strip. COVID-19 response plans in malnourished countries, vulnerable to fatal COVID-19, should incorporate food security, nutrition, and social protection as a priority component in order to reduce COVID-19 fatality.

Estimating under-reporting of COVID-19 cases in Indian states: an approach using a delay-adjusted case fatality ratio

OBJECTIVES

The COVID-19 pandemic has spread to all states in India. Due to limitations in testing coverage, the true extent of the spread may not be fully reflected in the reported cases. In this study, we obtain time-varying estimates of the fraction of COVID-19 infections reported in the different states.

METHODS

Following a methodology developed in prior work, we use a delay-adjusted case fatality ratio to estimate the true fraction of cases reported in different states. We also develop a delay adjusted test positivity estimation method and study the relationship between the estimated test positivity rate for each state and the estimated fraction of cases reported.

SETTING

We apply this method of analysis to all Indian states reporting at least 100 deaths as of 10 October 2020.

RESULTS

Our analysis suggests that delay-adjusted case fatality ratios observed in different states range from 0.47% to 3.55%. The estimated fraction of cases reported in different states ranges from 39% to 100% for an assumed baseline case fatality ratio of 1.38%, from 18.6% to 100% for an assumed baseline case fatality ratio of 0.66%, and from 2.8% to 19.7% for an assumed baseline case fatality ratio of 0.1%. We also demonstrate a statistically significant negative relationship between the fraction of cases reported in each state and the testing positivity rate.

CONCLUSIONS

The estimates provide a means to quantify and compare the trends of reporting and the true level of current infections in different states. This information may be used to guide policies for prioritising testing in different states, and also to analyse the time-varying effects of different quarantine measures adopted in different states.

Using excess deaths and testing statistics to improve estimates of COVID-19 mortalities

Factors such as non-uniform definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US is 13% higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find negligible or negative excess deaths for part and all of 2020 for Denmark, Germany, and Norway.

Interdisciplinary Approaches to COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has been a significant concern worldwide. The pandemic has demonstrated that public health issues are not merely a health concern but also affect society as a whole. In this chapter, we address the importance of bringing together the world's scientists to find appropriate solutions for controlling and managing the COVID-19 pandemic. Interdisciplinary cooperation, through modern scientific methods, could help to handle the consequences of the pandemic and to avoid the recurrence of future pandemics.

Global perspective of COVID-19 epidemiology for a full-cycle pandemic

As of October 2020, there are >1 million documented deaths with COVID-19. Excess deaths can be caused by both COVID-19 and the measures taken. COVID-19 shows extremely strong risk stratification across age, socioeconomic factors, and clinical factors. Calculation of years-of-life-lost from COVID-19 is methodologically challenging and can yield misleading over-estimates. Many early deaths may have been due to suboptimal management, malfunctional health systems, hydroxychloroquine, sending COVID-19 patients to nursing homes, and nosocomial infections; such deaths are partially avoidable moving forward. About 10% of the global population may be infected by October 2020. Global infection fatality rate is 0.15-0.20% (0.03-0.04% in those <70 years), with large variability across locations with different age-structure, institutionalization rates, socioeconomic inequalities, population-level clinical risk profile, public health measures, and health care. There is debate on whether at least 60% of the global population must be infected for herd immunity, or, conversely, mixing heterogeneity and pre-existing cross-immunity may allow substantially lower thresholds. Simulations are presented with a total of 1.58-8.76 million COVID-19 deaths over 5-years (1/2020-12/2024) globally (0.5-2.9% of total global deaths). The most favorable figures in that range would be feasible if high risk groups can be preferentially protected with lower infection rates than the remaining population. Death toll may also be further affected by potential availability of effective vaccines and treatments, optimal management and measures taken, COVID-19 interplay with influenza and other health problems, reinfection potential, and any chronic COVID-19 consequences. Targeted, precise management of the pandemic and avoiding past mistakes would help minimize mortality.

Visualizing the invisible: The effect of asymptomatic transmission on the outbreak dynamics of COVID-19

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.

Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications

Determine age-specific infection fatality rates for COVID-19 to inform public health policies and communications that help protect vulnerable age groups. Studies of COVID-19 prevalence were collected by conducting an online search of published articles, preprints, and government reports that were publicly disseminated prior to 18 September 2020. The systematic review encompassed 113 studies, of which 27 studies (covering 34 geographical locations) satisfied the inclusion criteria and were included in the meta-analysis. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities 4 weeks after the midpoint date of the study, reflecting typical lags in fatalities and reporting. Meta-regression procedures in Stata were used to analyze the infection fatality rate (IFR) by age. Our analysis finds a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFR is very low for children and younger adults (e.g., 0.002% at age 10 and 0.01% at age 25) but increases progressively to 0.4% at age 55, 1.4% at age 65, 4.6% at age 75, and 15% at age 85. Moreover, our results indicate that about 90% of the variation in population IFR across geographical locations reflects differences in the age composition of the population and the extent to which relatively vulnerable age groups were exposed to the virus. These results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.

Infection fatality risk for SARS-CoV-2 in community dwelling population of Spain: nationwide seroepidemiological study

OBJECTIVE

To estimate the infection fatality risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), based on deaths with confirmed coronavirus disease 2019 (covid-19) and excess deaths from all causes.

DESIGN

Nationwide seroepidemiological study.

SETTING

First wave of covid-19 pandemic in Spain.

PARTICIPANTS

Community dwelling individuals of all ages.

MAIN OUTCOME MEASURES

The main outcome measure was overall, and age and sex specific, infection fatality risk for SARS-CoV-2 (the number of covid-19 deaths and excess deaths divided by the estimated number of SARS-CoV-2 infections) in the community dwelling Spanish population. Deaths with laboratory confirmed covid-19 were obtained from the National Epidemiological Surveillance Network (RENAVE) and excess all cause deaths from the Monitoring Mortality System (MoMo), up to 15 July 2020. SARS-CoV-2 infections in Spain were derived from the estimated seroprevalence by a chemiluminescent microparticle immunoassay for IgG antibodies in 61 098 participants in the ENE-COVID nationwide seroepidemiological survey between 27 April and 22 June 2020.

RESULTS

The overall infection fatality risk was 0.8% (19 228 of 2.3 million infected individuals, 95% confidence interval 0.8% to 0.9%) for confirmed covid-19 deaths and 1.1% (24 778 of 2.3 million infected individuals, 1.0% to 1.2%) for excess deaths. The infection fatality risk was 1.1% (95% confidence interval 1.0% to 1.2%) to 1.4% (1.3% to 1.5%) in men and 0.6% (0.5% to 0.6%) to 0.8% (0.7% to 0.8%) in women. The infection fatality risk increased sharply after age 50, ranging from 11.6% (8.1% to 16.5%) to 16.4% (11.4% to 23.2%) in men aged 80 or more and from 4.6% (3.4% to 6.3%) to 6.5% (4.7% to 8.8%) in women aged 80 or more.

CONCLUSION

The increase in SARS-CoV-2 infection fatality risk after age 50 appeared to be more noticeable in men than in women. Based on the results of this study, fatality from covid-19 was greater than that reported for other common respiratory diseases, such as seasonal influenza.

COVID-19: Look to the Future, Learn from the Past

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

Data-driven modeling of COVID-19-Lessons learned

Understanding the outbreak dynamics of COVID-19 through the lens of mathematical models is an elusive but significant goal. Within only half a year, the COVID-19 pandemic has resulted in more than 19 million reported cases across 188 countries with more than 700,000 deaths worldwide. Unlike any other disease in history, COVID-19 has generated an unprecedented volume of data, well documented, continuously updated, and broadly available to the general public. Yet, the precise role of mathematical modeling in providing quantitative insight into the COVID-19 pandemic remains a topic of ongoing debate. Here we discuss the lessons learned from six month of modeling COVID-19. We highlight the early success of classical models for infectious diseases and show why these models fail to predict the current outbreak dynamics of COVID-19. We illustrate how data-driven modeling can integrate classical epidemiology modeling and machine learning to infer critical disease parameters-in real time-from reported case data to make informed predictions and guide political decision making. We critically discuss questions that these models can and cannot answer and showcase controversial decisions around the early outbreak dynamics, outbreak control, and exit strategies. We anticipate that this summary will stimulate discussion within the modeling community and help provide guidelines for robust mathematical models to understand and manage the COVID-19 pandemic. EML webinar speakers, videos, and overviews are updated at https://imechanica.org/node/24098.

SARS-CoV-2 Infections in the World: An Estimation of the Infected Population and a Measure of How Higher Detection Rates Save Lives

This paper provides an estimation of the accumulated detection rates and the accumulated number of infected individuals by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Worldwide, on July 20, it has been estimated above 160 million individuals infected by SARS-CoV-2. Moreover, it is found that only about 1 out of 11 infected individuals are detected. In an information context in which population-based seroepidemiological studies are not frequently available, this study shows a parsimonious alternative to provide estimates of the number of SARS-CoV-2 infected individuals. By comparing our estimates with those provided by the population-based seroepidemiological ENE-COVID study in Spain, we confirm the utility of our approach. Then, using a cross-country regression, we investigated if differences in detection rates are associated with differences in the cumulative number of deaths. The hypothesis investigated in this study is that higher levels of detection of SARS-CoV-2 infections can reduce the risk exposure of the susceptible population with a relatively higher risk of death. Our results show that, on average, detecting 5 instead of 35 percent of the infections is associated with multiplying the number of deaths by a factor of about 6. Using this result, we estimated that 120 days after the pandemic outbreak, if the US would have tested with the same intensity as South Korea, about 85,000 out of their 126,000 reported deaths could have been avoided.

Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters

OBJECTIVE

To provide estimates of the relative rate of COVID-19 death in people <65 years old versus older individuals in the general population, the absolute risk of COVID-19 death at the population level during the first epidemic wave, and the proportion of COVID-19 deaths in non-elderly people without underlying diseases in epicenters of the pandemic.

ELIGIBLE DATA

Cross-sectional survey of countries and US states with at least 800 COVID-19 deaths as of April 24, 2020 and with information on the number of deaths in people with age <65. Data were available for 14 countries (Belgium, Canada, France, Germany, India, Ireland, Italy, Mexico, Netherlands, Portugal, Spain, Sweden, Switzerland, UK) and 13 US states (California, Connecticut, Florida, Georgia, Illinois, Indiana, Louisiana, Maryland, Massachusetts, Michigan, New Jersey, New York, Pennsylvania). We also examined available data on COVID-19 deaths in people with age <65 and no underlying diseases.

MAIN OUTCOME MEASURES

Proportion of COVID-19 deaths in people <65 years old; relative mortality rate of COVID-19 death in people <65 versus ≥65 years old; absolute risk of COVID-19 death in people <65 and in those ≥80 years old in the general population as of June 17, 2020; absolute COVID-19 mortality rate expressed as equivalent of mortality rate from driving a motor vehicle.

RESULTS

Individuals with age <65 account for 4.5-11.2% of all COVID-19 deaths in European countries and Canada, 8.3-22.7% in the US locations, and were the majority in India and Mexico. People <65 years old had 30- to 100-fold lower risk of COVID-19 death than those ≥65 years old in 11 European countries and Canada, 16- to 52-fold lower risk in US locations, and less than 10-fold in India and Mexico. The absolute risk of COVID-19 death as of June 17, 2020 for people <65 years old in high-income countries ranged from 10 (Germany) to 349 per million (New Jersey) and it was 5 per million in India and 96 per million in Mexico. The absolute risk of COVID-19 death for people ≥80 years old ranged from 0.6 (Florida) to 17.5 per thousand (Connecticut). The COVID-19 mortality rate in people <65 years old during the period of fatalities from the epidemic was equivalent to the mortality rate from driving between 4 and 82 miles per day for 13 countries and 5 states, and was higher (equivalent to the mortality rate from driving 106-483 miles per day) for 8 other states and the UK. People <65 years old without underlying predisposing conditions accounted for only 0.7-3.6% of all COVID-19 deaths in France, Italy, Netherlands, Sweden, Georgia, and New York City and 17.7% in Mexico.

CONCLUSIONS

People <65 years old have very small risks of COVID-19 death even in pandemic epicenters 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.

Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters

OBJECTIVE

To provide estimates of the relative rate of COVID-19 death in people <65 years old versus older individuals in the general population, the absolute risk of COVID-19 death at the population level during the first epidemic wave, and the proportion of COVID-19 deaths in non-elderly people without underlying diseases in epicenters of the pandemic.

ELIGIBLE DATA

Cross-sectional survey of countries and US states with at least 800 COVID-19 deaths as of April 24, 2020 and with information on the number of deaths in people with age <65. Data were available for 14 countries (Belgium, Canada, France, Germany, India, Ireland, Italy, Mexico, Netherlands, Portugal, Spain, Sweden, Switzerland, UK) and 13 US states (California, Connecticut, Florida, Georgia, Illinois, Indiana, Louisiana, Maryland, Massachusetts, Michigan, New Jersey, New York, Pennsylvania). We also examined available data on COVID-19 deaths in people with age <65 and no underlying diseases.

MAIN OUTCOME MEASURES

Proportion of COVID-19 deaths in people <65 years old; relative mortality rate of COVID-19 death in people <65 versus ≥65 years old; absolute risk of COVID-19 death in people <65 and in those ≥80 years old in the general population as of June 17, 2020; absolute COVID-19 mortality rate expressed as equivalent of mortality rate from driving a motor vehicle.

RESULTS

Individuals with age <65 account for 4.5-11.2% of all COVID-19 deaths in European countries and Canada, 8.3-22.7% in the US locations, and were the majority in India and Mexico. People <65 years old had 30- to 100-fold lower risk of COVID-19 death than those ≥65 years old in 11 European countries and Canada, 16- to 52-fold lower risk in US locations, and less than 10-fold in India and Mexico. The absolute risk of COVID-19 death as of June 17, 2020 for people <65 years old in high-income countries ranged from 10 (Germany) to 349 per million (New Jersey) and it was 5 per million in India and 96 per million in Mexico. The absolute risk of COVID-19 death for people ≥80 years old ranged from 0.6 (Florida) to 17.5 per thousand (Connecticut). The COVID-19 mortality rate in people <65 years old during the period of fatalities from the epidemic was equivalent to the mortality rate from driving between 4 and 82 miles per day for 13 countries and 5 states, and was higher (equivalent to the mortality rate from driving 106-483 miles per day) for 8 other states and the UK. People <65 years old without underlying predisposing conditions accounted for only 0.7-3.6% of all COVID-19 deaths in France, Italy, Netherlands, Sweden, Georgia, and New York City and 17.7% in Mexico.

CONCLUSIONS

People <65 years old have very small risks of COVID-19 death even in pandemic epicenters 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.

Visualizing the invisible: The effect of asymptomatic transmission on the outbreak dynamics of COVID-19

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.

Risk of death by age and gender from CoVID-19 in Peru, March-May, 2020

Peru implemented strict social distancing measures during the early phase of the epidemic and is now experiencing one of the largest CoVID-19 epidemics in Latin America. Estimates of disease severity are an essential indicator to inform policy decisions about the intensity and duration of interventions needed to mitigate the outbreak. Here we derive delay-adjusted case fatality risks (aCFR) of CoVID-19 in a middle-income country in South America.We utilize government-reported time series of CoVID-19 cases and deaths in Peru stratified by age group and gender.As of May 25, 2020, we estimate the aCFR for men and women at 10.8% (95%CrI: 10.5-11.1%) and 6.5% (95%CrI: 6.2-6.8%), respectively, whereas the overall aCFR was estimated at 9.1% (95%CrI: 8.9-9.3%). Our results show that senior individuals have been the most severely affected by CoVID-19, particularly men, with an aCFR of nearly 60% for those aged 80- years. We also found that men have a significantly higher cumulative morbidity ratio across most age groups (proportion test, p-value< 0.001), with the exception of those aged 0-9 years.The ongoing CoVID-19 pandemic is generating a substantial mortality burden in Peru. Senior individuals, especially those older than 70 years, are being disproportionately affected by the CoVID-19 pandemic.

Early epidemiological assessment of the transmission potential and virulence of coronavirus disease 2019 (COVID-19) in Wuhan City, China, January-February, 2020

BACKGROUND

Since the first cluster of cases was identified in Wuhan City, China, in December 2019, coronavirus disease 2019 (COVID-19) rapidly spreads globally. Scientists have made strides in estimating key transmission and epidemiological parameters. In particular, accumulating evidence points to a substantial fraction of asymptomatic or subclinical infections, which influences our understanding of the transmission potential and severity of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.

METHODS

We employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory-confirmed COVID-19 cases and deaths in Wuhan City together with epidemiological data of Japanese repatriated from Wuhan City on board government-chartered flights were integrated into our analysis.

RESULTS

Our posterior estimates of basic reproduction number (R) in Wuhan City, China, in 2019-2020 reached values at 3.49 (95% CrI 3.39-3.62) with a mean serial interval of 6.0 days, and the enhanced public health intervention after January 23 in 2020 was associated with a significantly reduced R at 0.84 (95% CrI 0.81-0.88), with the total number of infections (i.e., cumulative infections) estimated at 1,906,634 (95% CrI 1,373,500-2,651,124) in Wuhan City, elevating the overall proportion of infected individuals to 19.1% (95% CrI 13.5-26.6%). We also estimated the most recent crude infection fatality ratio (IFR) and time-delay adjusted IFR at 0.04% (95% CrI 0.03-0.06%) and 0.12% (95% CrI 0.08-0.17%), respectively, estimates that are substantially smaller than the crude CFR estimated at 4.06%.

CONCLUSIONS

We have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China, during January-February 2020 using an ecological modeling approach that is suitable to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems. Our estimate of time-delay adjusted IFR falls in the range of the median IFR estimates based on multiple serological studies conducted in several areas of the world.

Evaluation of two commercial and two non-commercial immunoassays for the detection of prior infection to SARS-CoV-2

Background Seroepidemiology is an important tool to characterize the epidemiology and immunobiology of SARS-CoV-2 but many immunoassays have not been externally validated raising questions about reliability of study findings. To ensure meaningful data, particularly in a low seroprevalence population, assays need to be rigorously characterized with high specificity. Methods We evaluated two commercial (Roche Diagnostics and Epitope Diagnostics IgM/IgG) and two non-commercial (Simoa and Ragon/MGH IgG) immunoassays against 68 confirmed positive and 232 pre-pandemic negative controls. Sensitivity was stratified by time from symptom onset. The Simoa multiplex assay applied three pre-defined algorithm models to determine sample result. Results The Roche and Ragon/MGH IgG assays each registered 1/232 false positive, the primary Simoa model registered 2/232 false positives, and the Epitope registered 2/230 and 3/230 false positives for the IgG and IgM assays respectively. Sensitivity >21 days post symptom-onset was 100% for all assays except Epitope IgM, but lower and/or with greater variability between assays for samples collected 9-14 days (67-100%) and 15-21 days (69-100%) post-symptom onset. The Simoa and Epitope IgG assays demonstrated excellent sensitivity earlier in the disease course. The Roche and Ragon/MGH IgG assays were less sensitive during early disease, particularly among immunosuppressed individuals. Conclusions The Epitope IgG demonstrated good sensitivity and specificity. The Roche and Ragon/MGH IgG assays registered rare false positives with lower early sensitivity. The Simoa assay primary model had excellent sensitivity and few false positives.