Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control (preprint)

SARS-CoV-2 vaccines were developed and distributed during a global crisis at unprecedented speed. Still, little is known about trends in vaccine uptake over time, their association with socioeconomic inequality, and the impact of these temporal trends on disease control. By analyzing data from dozens of countries, we examined vaccination rates across high and low socioeconomic (SES) groups, showing that socioeconomic disparities in the fraction of the population vaccinated exist at both national and sub-national levels. We also identified two distinct vaccination trends: one characterized by rapid initial roll-out, quickly reaching a plateau; and another trend that is sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences across the two vaccination types in the burden of infections and deaths. The timing of initial roll-out has a more significant effect on transmission and deaths than the eventual level of coverage or the degree of SES disparity. Surprisingly, the speed of the roll-out is not associated with wealth inequality or GDP per capita of countries. While socioeconomic disparity should be addressed, accelerating the initial roll-out for all groups is a broadly accessible intervention and has the potential to minimize the burden of infections and deaths across socioeconomic groups.

All-cause excess mortality in the State of Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021) (preprint)

Official COVID-19 mortality statistics are strongly influenced by the local diagnostic capacity, strength of the healthcare system, and the recording and reporting capacities on causes of death. This can result in significant undercounting of COVID-19 attributable deaths, making it challenging to understand the total mortality burden of the pandemic. Excess mortality, which is defined as the increase in observed death counts compared to a baseline expectation, provides an alternate measure of the mortality shock of the COVID-19 pandemic. Here, we use data from civil death registers for 54 municipalities across the state of Gujarat, India, to estimate the impact of the COVID-19 pandemic on all-cause mortality. Using a model fit to monthly data from January 2019 to February 2020, we estimate excess mortality over the course of the pandemic from March 2020 to April 2021. We estimated 16,000 [95% CI: 14,000, 18,000] excess deaths across these municipalities since March 2020. The sharpest increase in deaths was observed in April 2021, with an estimated 480% [95% CI: 390%, 580%] increase in mortality from expected counts for the same period. Females and the 40 to 60 age groups experienced a greater increase from baseline mortality compared to other demographic groups. Our excess mortality estimate for these 54 municipalities, representing approximately 5% of the state population, exceeds the official COVID-19 death count for the entire state of Gujarat.

Lives Saved from Age-Prioritized Covid-19 Vaccination (preprint)

BACKGROUND The criteria used to allocate scarce COVID-19 vaccines are hotly contested. While some are pushing just to get vaccines into arms as quickly as possible, others advocate prioritization in terms of risk. OBJECTIVE Our aim is to use demographic models to show the enormous potential of vaccine risk-prioritization in saving lives. METHODS We develop a simple mathematical model that accounts for the age distribution of the population and of COVID-19 mortality. This model considers only the direct live-savings for those who receive the vaccine, and does not account for possible indirect effects of vaccination. We apply this model to the United States, Japan, and Bangladesh. RESULTS In the United States, we find age-prioritization would reduce deaths during a vaccine campaign by about 93 percent relative to no vaccine and 85 percent relative to age-neutral vaccine distribution. In countries with younger age structures, such as Bangladesh, the benefits of age-prioritization are even greater. CONTRIBUTION For policy makers, our findings give additional support to risk-prioritized allocation of COVID-19 vaccines. For demographers, our results show how the age-structures of the population and of disease mortality combine into an expression of risk concentration that shows the benefits of prioritized allocation. This measure can also be used to study the effects of prioritizing other dimensions of risk such as underlying health conditions.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile (preprint)

The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality –measured either by direct COVID-19 attributed deaths or excess deaths– and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials: (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.

Quantifying interpersonal contact in the United States during the spread of COVID-19: first results from the Berkeley Interpersonal Contact Study (preprint)

SARS-CoV-2 is transmitted primarily through close, person-to-person interactions. In the absence of a vaccine, interventions focused on physical distancing have been widely used to reduce community transmission. These physical distancing policies can only control the spread of SARS-CoV-2 if they are able to reduce the amount of close interpersonal contact in a population. To quantify the impact of these policies over the first months of the COVID-19 pandemic in the United States, we conducted three waves of contact surveys between March 22 and June 23, 2020. We find that rates of interpersonal contact have been dramatically reduced at all ages in the US, with an 82% (95% CI:80% - 83%) reduction in the average number of daily contacts observed during the first wave compared to pre-pandemic levels. We find that this decline reduced the reproduction number, R0, to below one in March and early April (0.66, 95% CI:0.35 - 0.88). However, with easing of physical distancing measures, we find increases in interpersonal contact rates over the subsequent two waves, pushing R0 above 1. We also find significant differences in numbers of reported contacts by age, gender, race and ethnicity. Certain demographic groups, including people under 45, males, and Black and Hispanic respondents, have significantly higher contact rates than the rest of the population. Tracking changes in interpersonal contact patterns can provide rapid assessments of the impact of physical distancing policies over the course of the pandemic and help identify at-risk populations.

Incidence, clinical outcomes, and transmission dynamics of hospitalized 2019 coronavirus disease among 9,596,321 individuals residing in California and Washington, United States: a prospective cohort study (preprint)

Background: The United States is now the country reporting the highest number of 2019 coronavirus disease (COVID-19) cases and deaths. However, little is known about the epidemiology and burden of severe COVID-19 to inform planning within healthcare systems and modeling of intervention impact. Methods: We assessed incidence, duration of hospitalization, and clinical outcomes of acute COVID-19 inpatient admissions in a prospectively-followed cohort of 9,596,321 individuals enrolled in comprehensive, integrated healthcare delivery plans from Kaiser Permanente in California and Washington state. We also estimated the effective reproductive number (RE) describing transmission in the study populations. Results: Data covered 1277 hospitalized patients with laboratory- or clinically-confirmed COVID-19 diagnosis by April 9, 2020. Cumulative incidence of first COVID-19 acute inpatient admission was 10.6-12.4 per 100,000 cohort members across the study regions. Mean censoring-adjusted duration of hospitalization was 10.7 days (2.5-97.5%iles: 0.8-30.1) among survivors and 13.7 days (2.5-97.5%iles: 1.7-34.6) among non-survivors. Among all hospitalized confirmed cases, censoring-adjusted probabilities of ICU admission and mortality were 41.9% (95% confidence interval: 34.1-51.4%) and 17.8% (14.3-22.2%), respectively, and higher among men than women. We estimated RE was 1.43 (1.17-1.73), 2.09 (1.63-2.69), and 1.47 (0.07-2.59) in Northern California, Southern California, and Washington, respectively, for infections acquired March 1, 2020. RE declined to 0.98 (0.76-1.27), 0.89 (0.74-1.06), and 0.92 (0.05-1.55) respectively, for infections acquired March 20, 2020. Conclusions: We identify high probability of ICU admission, long durations of stay, and considerable mortality risk among hospitalized COVID-19 cases in the western United States. Reductions in RE have occurred in conjunction with implementation of non-pharmaceutical interventions.