Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India.

This cross-sectional study examines prepandemic-to-postpandemic changes in mortality, nutrition and feeding practices, anthropometry, vaccination, and other measures in a sample of children from the Indian National Family Health Survey.

Uncovering inequities in Covid-19 vaccine coverage for adults and elderly in Brazil: A multilevel study of 2021-2022 data.

Vaccination is crucial for reducing severe COVID-19 cases, hospitalizations, and deaths. However, vaccine access disparities within countries, particularly in low- and middle-income nations, may leave disadvantaged regions and populations behind. This study aimed to investigate potential inequalities in vaccine coverage among Brazilian aged 18 years and older based on demographic, geographic, and socioeconomic characteristics at the municipal level. A total of 389 million vaccination records from the National Immunization Program Information System were analyzed to calculate vaccine coverage rates for the first, second, and booster doses among adults (18-59 years) and elderly (60 + years) vaccinated between January 2021 and December 2022. We analyzed the data by gender and used a three-level (municipalities, states, regions) multilevel regression analysis to assess the association between vaccine coverage and municipal characteristics. Vaccination coverage was higher among the elderly than among adults, particularly for the second and booster doses. Adult women showed higher coverage rates than men (ranging from 118 % to 25 % higher along the analyzed period). Significant inequalities were observed when analyzing the evolution of vaccination coverage by sociodemographic characteristics of municipalities. In the early stages of the vaccination campaign, municipalities with higher per capita Gross Domestic Product (pGDP), educational level, and fewer Black residents reached higher population coverages earlier. In December 2022, adult and elderly booster vaccine coverage was 43 % and 19 %, respectively, higher in municipalities in the highest quintile of educational level. Higher vaccine uptake was also observed in municipalities with fewer Black residents and higher pGDP. Municipalities accounted for most of the variance in vaccine coverage (59.7 %-90.4 % depending on the dose and age group). This study emphasizes the inadequate booster coverage and the presence of socioeconomic and demographic disparities in COVID-19 vaccination rates. These issues must be addressed through equitable interventions to avoid potential disparities in morbidity and mortality.

The Psychological Costs of the COVID-19 Pandemic and Heterogeneous Effects in South Korea: Evidence from a Difference-in-Differences Analysis.

This study estimates the effects of the COVID-19 pandemic on life satisfaction and stress and examines whether these effects vary across different sociodemographic groups using a nationally representative sample in South Korea. We estimate the causal effects of COVID-19 on psychological well-being by exploiting regional variation in the spread of the pandemic in South Korea. While the number of confirmed cases was very small in other provinces in the first half of 2020, the coronavirus spread rapidly in Daegu after an outbreak in one church. We employ a difference-in-differences approach that compares changes in people's life satisfaction and stress before-and-after the initial surge of COVID-19 cases in Daegu and other provinces. Our results show that the proportion of people who are dissatisfied with life increased by 2.8-6.5 percentage points more in Daegu than in other provinces after the COVID-19 outbreak. During the same period, the proportion of people who reported feeling stressed increased more in Daegu than in other provinces by 5.8-8.9 percentage points. Our results also suggest that the negative impact of the COVID-19 outbreak on psychological well-being is significantly greater for men, young adults, middle-aged adults, self-employed workers, and middle-income individuals. On the other hand, the proportion of people who report feeling stressed among the highest-educated (a master's degree or higher) and high-income individuals decreased after the onset of the COVID-19 outbreak.

The Psychological Costs of the COVID-19 Pandemic and Heterogeneous Effects in South Korea: Evidence from a Difference-in-Differences Analysis

This study estimates the effects of the COVID-19 pandemic on life satisfaction and stress and examines whether these effects vary across different sociodemographic groups using a nationally representative sample in South Korea. We estimate the causal effects of COVID-19 on psychological well-being by exploiting regional variation in the spread of the pandemic in South Korea. While the number of confirmed cases was very small in other provinces in the first half of 2020, the coronavirus spread rapidly in Daegu after an outbreak in one church. We employ a difference-in-differences approach that compares changes in people’s life satisfaction and stress before-and-after the initial surge of COVID-19 cases in Daegu and other provinces. Our results show that the proportion of people who are dissatisfied with life increased by 2.8–6.5 percentage points more in Daegu than in other provinces after the COVID-19 outbreak. During the same period, the proportion of people who reported feeling stressed increased more in Daegu than in other provinces by 5.8–8.9 percentage points. Our results also suggest that the negative impact of the COVID-19 outbreak on psychological well-being is significantly greater for men, young adults, middle-aged adults, self-employed workers, and middle-income individuals. On the other hand, the proportion of people who report feeling stressed among the highest-educated (a master’s degree or higher) and high-income individuals decreased after the onset of the COVID-19 outbreak.

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases.

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%-32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%-16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%-145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

Assessing the prevalence of young children living in households prepared for COVID-19 in 56 low- and middle-income countries.

BACKGROUND: The COVID-19 pandemic and governments' attempts to contain it are negatively affecting young children's health and development in ways we are only beginning to understand and measure. Responses to the pandemic are driven largely by confining children and families to their homes. This study aims to assess the levels of and associated socioeconomic disparities in household preparedness for protecting young children under the age of five from being exposed to communicable diseases, such as COVID-19, in low- and middle-income countries (LMICs). METHODS: Using data from nationally representative household surveys in 56 LMICs since 2016, we estimated the percentages of young children under the age of five living in households prepared for communicable diseases (e.g., COVID-19) and associated residential and wealth disparities at the country- and aggregate-level. Preparedness was defined on the basis of space for quarantine, adequacy of toilet facilities and hand hygiene, mass media exposure at least once a week, and phone ownership. Disparities within countries were measured as the absolute gap in two domains-household wealth and residential area - and compared across regions and country income groups. RESULTS: The final data set included 766,313 children under age five. On average, 19.4% of young children in the 56 countries lived in households prepared for COVID-19, ranging from 0.6% in Ethiopia in 2016 to 70.9% in Tunisia in 2018. In close to 90% of countries (50), fewer than 50% of young children lived in prepared households. Young children in rural areas or in the poorest households were less likely to live in prepared households than their counterparts. CONCLUSIONS: A large portion of young children under the age of five in LMICs were living in households that did not meet all preparedness guidelines for preventing COVID-19 and caring for patients at home. This study highlights the need to ensure all families in LMICs have the means to prevent the spread of the pandemic or other communicable illnesses to young children during pandemics.

Neighborhood socioeconomic inequality based on everyday mobility predicts COVID-19 infection in San Francisco, Seattle, and Wisconsin.

Race and class disparities in COVID-19 cases are well documented, but pathways of possible transmission by neighborhood inequality are not. This study uses administrative data on COVID-19 cases for roughly 2000 census tracts in Wisconsin, Seattle/King County, and San Francisco to analyze how neighborhood socioeconomic (dis)advantage predicts cumulative caseloads through February 2021. Unlike past research, we measure a neighborhood's disadvantage level using both its residents' demographics and the demographics of neighborhoods its residents visit and are visited by, leveraging daily mobility data from 45 million mobile devices. In all three jurisdictions, we find sizable disparities in COVID-19 caseloads. Disadvantage in a neighborhood's mobility network has greater impact than its residents' socioeconomic characteristics. We also find disparities by neighborhood racial/ethnic composition, which can be explained, in part, by residential and mobility-based disadvantage. Neighborhood conditions measured before a pandemic offer substantial predictive power for subsequent incidence, with mobility-based disadvantage playing an important role.

Mobility restrictions were associated with reductions in COVID-19 incidence early in the pandemic: evidence from a real-time evaluation in 34 countries.

Most countries have implemented restrictions on mobility to prevent the spread of Coronavirus disease-19 (COVID-19), entailing considerable societal costs but, at least initially, based on limited evidence of effectiveness. We asked whether mobility restrictions were associated with changes in the occurrence of COVID-19 in 34 OECD countries plus Singapore and Taiwan. Our data sources were the Google Global Mobility Data Source, which reports different types of mobility, and COVID-19 cases retrieved from the dataset curated by Our World in Data. Beginning at each country's 100th case, and incorporating a 14-day lag to account for the delay between exposure and illness, we examined the association between changes in mobility (with January 3 to February 6, 2020 as baseline) and the ratio of the number of newly confirmed cases on a given day to the total number of cases over the past 14 days from the index day (the potentially infective 'pool' in that population), per million population, using LOESS regression and logit regression. In two-thirds of examined countries, reductions of up to 40% in commuting mobility (to workplaces, transit stations, retailers, and recreation) were associated with decreased cases, especially early in the pandemic. Once both mobility and incidence had been brought down, further restrictions provided little additional benefit. These findings point to the importance of acting early and decisively in a pandemic.

The evolution of the association between community level social capital and COVID-19 deaths and hospitalizations in the United States.

We use county level data from the United States to document the role of social capital the evolution of COVID-19 between January 2020 and January 2021. We find that social capital differentials in COVID-19 deaths and hospitalizations depend on the dimension of social capital and the timeframe considered. Communities with higher levels of relational and cognitive social capital were especially successful in lowering COVID-19 deaths and hospitalizations than communities with lower social capital between late March and early April. A difference of one standard deviation in relational social capital corresponded to a reduction of 30% in the number of COVID-19 deaths recorded. After April 2020, differentials in COVID-19 deaths related to relational social capital persisted although they became progressively less pronounced. By contrast, the period of March-April 2020, our estimates suggest that there was no statistically significant difference in the number of deaths recorded in areas with different levels of cognitive social capital. In fact, from late June-early July onwards the number of new deaths recorded as being due to COVID-19 was higher in communities with higher levels of cognitive social capital. The overall number of deaths recorded between January 2020 and January 2021 was lower in communities with higher levels of relational social capital. Our findings suggest that the association between social capital and public health outcomes can vary greatly over time and across indicators of social capital.

Association of Human Mobility Restrictions and Race/Ethnicity-Based, Sex-Based, and Income-Based Factors With Inequities in Well-being During the COVID-19 Pandemic in the United States.

Importance: An accurate understanding of the distributional implications of public health policies is critical for ensuring equitable responses to the COVID-19 pandemic and future public health threats. Objective: To identify and quantify the association of race/ethnicity-based, sex-based, and income-based inequities of state-specific lockdowns with 6 well-being dimensions in the United States. Design, Setting, and Participants: This pooled, repeated cross-sectional study used data from 14 187 762 households who participated in phase 1 of the population-representative US 2020 Household Pulse Survey (HPS). Households were invited to participate by email, text message, and/or telephone as many as 3 times. Data were collected via an online questionnaire from April 23 to July 21, 2020, and participants lived in all 50 US states and the District of Columbia. Exposures: Indicators of race/ethnicity, sex, and income and their intersections. Main Outcomes and Measures: Unemployment; food insufficiency; mental health problems; no medical care received for health problems; default on last month's rent or mortgage; and class cancellations with no distance learning. Race/ethnicity, sex, income, and their intersections were used to measure distributional implications across historically marginalized populations; state-specific, time-varying population mobility was used to measure lockdown intensity. Logistic regression models with pooled repeated cross-sections were used to estimate risk of dichotomous outcomes by social group, adjusted for confounding variables. Results: The 1 088 314 respondents (561 570 [51.6%; 95% CI, 51.4%-51.9%] women) were aged 18 to 88 years (mean [SD], 51.55 [15.74] years), and 826 039 (62.8%; 95% CI, 62.5%-63.1%) were non-Hispanic White individuals; 86 958 (12.5%; 95% CI, 12.4%-12.7%), African American individuals; 86 062 (15.2%; 95% CI, 15.0%-15.4%), Hispanic individuals; and 50 227 (5.6%; 95% CI, 5.5%-5.7%), Asian individuals. On average, every 10% reduction in mobility was associated with higher odds of unemployment (odds ratio [OR], 1.3; 95% CI, 1.2-1.4), food insufficiency (OR, 1.1; 95% CI, 1.1-1.2), mental health problems (OR, 1.04; 95% CI, 1.0-1.1), and class cancellations (OR, 1.1; 95% CI, 1.1-1.2). Across most dimensions compared with White men with high income, African American individuals with low income experienced the highest risks (eg, food insufficiency, men: OR, 3.3; 95% CI, 2.8-3.7; mental health problems, women: OR, 1.9; 95% CI, 1.8-2.1; medical care inaccessibility, women: OR, 1.7; 95% CI, 1.6-1.9; unemployment, men: OR, 2.8; 95% CI, 2.5-3.2; rent/mortgage defaults, men: OR, 5.7; 95% CI, 4.7-7.1). Other high-risk groups were Hispanic individuals (eg, unemployment, Hispanic men with low income: OR, 2.9; 95% CI, 2.5-3.4) and women with low income across all races/ethnicities (eg, medical care inaccessibility, non-Hispanic White women: OR, 1.8; 95% CI, 1.7-2.0). Conclusions and Relevance: In this cross-sectional study, African American and Hispanic individuals, women, and households with low income had higher odds of experiencing adverse outcomes associated with the COVID-19 pandemic and stay-at-home orders. Blanket public health policies ignoring existing distributions of risk to well-being may be associated with increased race/ethnicity-based, sex-based, and income-based inequities.

Forecasting efforts from prior epidemics and COVID-19 predictions.

Since the onset of the COVID-19 pandemic, countless disease prediction models have emerged, shaping the focus of news media, policymakers, and broader society. We reviewed the accuracy of forecasts made during prior twenty-first century epidemics, namely SARS, H1N1, and Ebola. We found that while disease prediction models were relatively nascent as a research focus during SARS and H1N1, for Ebola, numerous such forecasts were published. We found that forecasts of deaths for Ebola were often far from the eventual reality, with a strong tendency to over predict. Given the societal prominence of these models, it is crucial that their uncertainty be communicated. Otherwise, we will be unaware if we are being falsely lulled into complacency or unjustifiably shocked into action.