Global population profile of tropical cyclone exposure from 2002 to 2019.

Tropical cyclones have far-reaching impacts on livelihoods and population health that often persist years after the event1-4. Characterizing the demographic and socioeconomic profile and the vulnerabilities of exposed populations is essential to assess health and other risks associated with future tropical cyclone events5. Estimates of exposure to tropical cyclones are often regional rather than global6 and do not consider population vulnerabilities7. Here we combine spatially resolved annual demographic estimates with tropical cyclone wind fields estimates to construct a global profile of the populations exposed to tropical cyclones between 2002 and 2019. We find that approximately 560 million people are exposed yearly and that the number of people exposed has increased across all cyclone intensities over the study period. The age distribution of those exposed has shifted away from children (less than 5 years old) and towards older people (more than 60 years old) in recent years compared with the early 2000s. Populations exposed to tropical cyclones are more socioeconomically deprived than those unexposed within the same country, and this relationship is more pronounced for people exposed to higher-intensity storms. By characterizing the patterns and vulnerabilities of exposed populations, our results can help identify mitigation strategies and assess the global burden and future risks of tropical cyclones.

Emergency department visits respond nonlinearly to wildfire smoke.

Air pollution negatively affects a range of health outcomes. Wildfire smoke is an increasingly important contributor to air pollution, yet wildfire smoke events are highly salient and could induce behavioral responses that alter health impacts. We combine geolocated data covering all emergency department (ED) visits to nonfederal hospitals in California from 2006 to 2017 with spatially resolved estimates of daily wildfire smoke PM[Formula: see text] concentrations and quantify how smoke events affect ED visits. Total ED visits respond nonlinearly to smoke concentrations. Relative to a day with no smoke, total visits increase by 1 to 1.5% in the week following low or moderate smoke days but decline by 6 to 9% following extreme smoke days. Reductions persist for at least a month. Declines at extreme levels are driven by diagnoses not thought to be acutely impacted by pollution, including accidental injuries and several nonurgent symptoms, and declines come disproportionately from less-insured populations. In contrast, health outcomes with the strongest physiological link to short-term air pollution increase dramatically in the week following an extreme smoke day: We estimate that ED visits for asthma, COPD, and cough all increase by 30 to 110%. Data from internet searches, vehicle traffic sensors, and park visits indicate behavioral changes on high smoke days consistent with declines in healthcare utilization. Because low and moderate smoke days vastly outweigh high smoke days, we estimate that smoke was responsible for an average of 3,010 (95% CI: 1,760-4,380) additional ED visits per year 2006 to 2017. Given the increasing intensity of wildfire smoke events, behavioral mediation is likely to play a growing role in determining total smoke impacts.

Massive covidization of research citations and the citation elite.

Massive scientific productivity accompanied the COVID-19 pandemic. We evaluated the citation impact of COVID-19 publications relative to all scientific work published in 2020 to 2021 and assessed the impact on scientist citation profiles. Using Scopus data until August 1, 2021, COVID-19 items accounted for 4% of papers published, 20% of citations received to papers published in 2020 to 2021, and >30% of citations received in 36 of the 174 disciplines of science (up to 79.3% in general and internal medicine). Across science, 98 of the 100 most-cited papers published in 2020 to 2021 were related to COVID-19; 110 scientists received ≥10,000 citations for COVID-19 work, but none received ≥10,000 citations for non-COVID-19 work published in 2020 to 2021. For many scientists, citations to their COVID-19 work already accounted for more than half of their total career citation count. Overall, these data show a strong covidization of research citations across science, with major impact on shaping the citation elite.

Robust relationship between air quality and infant mortality in Africa.

Poor air quality is thought to be an important mortality risk factor globally1-3, but there is little direct evidence from the developing world on how mortality risk varies with changing exposure to ambient particulate matter. Current global estimates apply exposure-response relationships that have been derived mostly from wealthy, mid-latitude countries to spatial population data4, and these estimates remain unvalidated across large portions of the globe. Here we combine household survey-based information on the location and timing of nearly 1 million births across sub-Saharan Africa with satellite-based estimates5 of exposure to ambient respirable particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) to estimate the impact of air quality on mortality rates among infants in Africa. We find that a 10 µg m-3 increase in PM2.5 concentration is associated with a 9% (95% confidence interval, 4-14%) rise in infant mortality across the dataset. This effect has not declined over the last 15 years and does not diminish with higher levels of household wealth. Our estimates suggest that PM2.5 concentrations above minimum exposure levels were responsible for 22% (95% confidence interval, 9-35%) of infant deaths in our 30 study countries and led to 449,000 (95% confidence interval, 194,000-709,000) additional deaths of infants in 2015, an estimate that is more than three times higher than existing estimates that attribute death of infants to poor air quality for these countries2,6. Upward revision of disease-burden estimates in the studied countries in Africa alone would result in a doubling of current estimates of global deaths of infants that are associated with air pollution, and modest reductions in African PM2.5 exposures are predicted to have health benefits to infants that are larger than most known health interventions.

Health and development from preconception to 20 years of age and human capital.

Optimal health and development from preconception to adulthood are crucial for human flourishing and the formation of human capital. The Nurturing Care Framework, as adapted to age 20 years, conceptualises the major influences during periods of development from preconception, through pregnancy, childhood, and adolescence that affect human capital. In addition to mortality in children younger than 5 years, stillbirths and deaths in 5-19-year-olds are important to consider. The global rate of mortality in individuals younger than 20 years has declined substantially since 2000, yet in 2019 an estimated 8·6 million deaths occurred between 28 weeks of gestation and 20 years of age, with more than half of deaths, including stillbirths, occurring before 28 days of age. The 1000 days from conception to 2 years of age are especially influential for human capital. The prevalence of low birthweight is high in sub-Saharan Africa and even higher in south Asia. Growth faltering, especially from birth to 2 years, occurs in most world regions, whereas overweight increases in many regions from the preprimary school period through adolescence. Analyses of cohort data show that growth trajectories in early years of life are strong determinants of nutritional outcomes in adulthood. The accrual of knowledge and skills is affected by health, nutrition, and home resources in early childhood and by educational opportunities in older children and adolescents. Linear growth in the first 2 years of life better predicts intelligence quotients in adults than increases in height in older children and adolescents. Learning-adjusted years of schooling range from about 4 years in sub-Saharan Africa to about 11 years in high-income countries. Human capital depends on children and adolescents surviving, thriving, and learning until adulthood.

Clostridium difficile and other adverse events from overprescribed antibiotics for acute upper respiratory infection.

BACKGROUND: Guidelines widely recommend avoiding antibiotics for many acute upper respiratory infections (aURIs) to avert adverse events in the absence of likely benefit. However, the extent of harm from these antibiotics remains a subject of debate and could inform patient-centered decision-making. Prior estimates finding a number needed to harm (NNH) between 8 and 10 rely on patient-reported adverse events of any severity. In this analysis, we sought to estimate adverse events by only measuring comparatively severe events that require subsequent clinical evaluation. METHODS: We constructed a retrospective cohort, including 51 million patient encounters. Using logistic regression models, we determined the adjusted odds ratio (aOR) of clinically detectable adverse events following antibiotic use compared with events among unexposed individuals with aURIs. Our outcomes included candidiasis, diarrhea, Clostridium difficile infection (CDI), and a composite outcome. FINDINGS: From our analysis, 62.4% of the population received antibiotics in an aURI encounter. Observed adverse events in the antibiotic-exposed group were 54,279 and 46,936 for diarrhea and candidiasis, respectively, yielding an aOR of 1.24 and 1.61, and an NNH of 3,126 and 1,975. Observed events of CDI in the exposed group were 30,133, and aORs of isolated CDI and combined adverse events were 1.07 and 1.30, resulting in an NNH of 17,695 and 1,150, respectively. Females were more likely to be diagnosed with any adverse event. Overall antibiotics were found to result in 5.7 additional cases of CDI per 100,000 outpatient prescriptions following an upper respiratory tract infection. INTERPRETATION: Despite higher NNH than previous methods of analysis, we find substantial iatrogenic harm associated with prescribing antibiotics in aURIs.

Clinical Outcomes, Echocardiographic Findings, and Care Quality Metrics for People Living With Human Immunodeficiency Virus (HIV) and Rheumatic Heart Disease in Uganda.

BACKGROUND: Rheumatic heart disease (RHD) affects 41 million people worldwide, mostly in low- and middle-income countries, where it is co-endemic with human immunodeficiency virus (HIV). HIV is also a chronic inflammatory disorder associated with cardiovascular complications, yet the epidemiology of patients affected by both diseases is poorly understood. METHODS: Utilizing the Uganda National RHD Registry, we described the echocardiographic findings, clinical characteristics, medication prescription rates, and outcomes of all 73 people carrying concurrent diagnoses of HIV and RHD between 2009 and 2018. These individuals were compared to an age- and sex-matched cohort of 365 subjects with RHD only. RESULTS: The median age of the HIV-RHD group was 36 years (interquartile range [IQR] 15), and 86% were women. The HIV-RHD cohort had higher rates of prior stroke/transient ischemic attack (12% vs 5%, P = .02) than the RHD-only group, with this association persisting following multivariable adjustment (odds ratio [OR] 3.08, P = .03). Prevalence of other comorbidities, echocardiographic findings, prophylactic penicillin prescription rates, retention in clinical care, and mortality were similar between the 2 groups. CONCLUSIONS: Patients living with RHD and HIV in Uganda are a relatively young, predominantly female group. Although RHD-HIV comorbid individuals have higher rates of stroke, their similar all-cause mortality and RHD care quality metrics (such as retention in care) compared to those with RHD alone suggest rheumatic heart disease defines their clinical outcome more than HIV does. We believe this study to be one of the first reports of the epidemiologic profile and longitudinal outcomes of patients who carry diagnoses of both conditions.

The effects of armed conflict on the health of women and children.

Women and children bear substantial morbidity and mortality as a result of armed conflicts. This Series paper focuses on the direct (due to violence) and indirect health effects of armed conflict on women and children (including adolescents) worldwide. We estimate that nearly 36 million children and 16 million women were displaced in 2017, on the basis of international databases of refugees and internally displaced populations. From geospatial analyses we estimate that the number of non-displaced women and children living dangerously close to armed conflict (within 50 km) increased from 185 million women and 250 million children in 2000, to 265 million women and 368 million children in 2017. Women's and children's mortality risk from non-violent causes increases substantially in response to nearby conflict, with more intense and more chronic conflicts leading to greater mortality increases. More than 10 million deaths in children younger than 5 years can be attributed to conflict between 1995 and 2015 globally. Women of reproductive ages living near high intensity conflicts have three times higher mortality than do women in peaceful settings. Current research provides fragmentary evidence about how armed conflict indirectly affects the survival chances of women and children through malnutrition, physical injuries, infectious diseases, poor mental health, and poor sexual and reproductive health, but major systematic evidence is sparse, hampering the design and implementation of essential interventions for mitigating the harms of armed conflicts.

The political and security dimensions of the humanitarian health response to violent conflict.

The nature of armed conflict throughout the world is intensely dynamic. Consequently, the protection of non-combatants and the provision of humanitarian services must continually adapt to this changing conflict environment. Complex political affiliations, the systematic use of explosive weapons and sexual violence, and the use of new communication technology, including social media, have created new challenges for humanitarian actors in negotiating access to affected populations and security for their own personnel. The nature of combatants has also evolved as armed, non-state actors might have varying motivations, use different forms of violence, and engage in a variety of criminal activities to generate requisite funds. New health threats, such as the COVID-19 pandemic, and new capabilities, such as modern trauma care, have also created new challenges and opportunities for humanitarian health provision. In response, humanitarian policies and practices must develop negotiation and safety capabilities, informed by political and security realities on the ground, and guidance from affected communities. More fundamentally, humanitarian policies will need to confront a changing geopolitical environment, in which traditional humanitarian norms and protections might encounter wavering support in the years to come.

Shifting the Demand for Vaccines: A Review of Strategies.

Vaccines prevent millions of deaths, and yet millions of people die each year from vaccine-preventable diseases. The primary reason for these deaths is that a significant fraction of the population chooses not to vaccinate. Why don't people vaccinate, and what can be done to increase vaccination rates besides providing free and easy access to vaccines? This review presents a conceptual framework, motivated by economic theory, of which factors shift the demand for vaccines. Next, it critically examines the literature on these demand shifters and interventions that target these demand shifters. The review concludes with offering directions for future research and lessons for public health decision making.

Systematic identification and replication of factors associated with human papillomavirus vaccine initiation among adolescents in the United States using an environment-wide association study approach.

OBJECTIVE: Human papillomavirus (HPV) vaccination coverage is low among adolescents in the USA. Identification of factors associated with HPV vaccine initiation (receipt of ≥1 dose) is critical for improving uptake. Our objective was to systematically investigate all eligible factors available in a nationally representative sample of adolescents to identify drivers of HPV vaccine initiation using a novel methodological approach. METHODS: We performed multiple cross-sectional analyses using data from the adolescent component of the National Immunization Surveys (NIS)-Teen between 2014 and 2019. Study participants were parents or caregivers of adolescents aged 13-17 years. Exposure variables measured sociodemographic and geographical characteristics, health conditions and healthcare provision. We tested the association between each factor and HPV vaccine initiation using univariate logistic regression and multivariate logistic regression adjusted for mother's age, mother's education level, mother's marital status, poverty status and adolescent's sex. We validated findings for each type of analysis within surveys, between surveys (across years 2014-2019) and across several subgroups (age, sex, poverty status and race/ethnicity). RESULTS: Six factors were replicated in the multivariate analysis. Most replicated factors characterised the role of healthcare providers and healthcare-seeking behaviours. After adjustment, provider HPV recommendation remained the most strongly associated with HPV vaccine initiation (2019 NIS-Teen: OR 13.4, 95% CI 11.3 to 17.3, p<0.001). The variance explained by a full model including replicated factors was 0.39. CONCLUSIONS: This is the first study to explore the association between all available factors in the NIS-Teen and HPV vaccine initiation in a systematic manner. Our study suggests that healthcare-seeking behaviours and interactions with the health system may be drivers of HPV vaccine initiation and warrant further study. Addressing these factors could improve the rate of HPV vaccine initiation among adolescents in the USA.

Racial and ethnic inequities in the early distribution of U.S. COVID-19 testing sites and mortality.

BACKGROUND: In 2020, early U.S. COVID-19 testing sites offered diagnostic capacity to patients and were important sources of epidemiological data about the spread of the novel pandemic disease. However, little research has comprehensively described American testing sites' distribution by race/ethnicity and sought to identify any relation to known disparities in COVID-19 outcomes. METHODS: Locations of U.S. COVID-19 testing sites were gathered from 16 April to 28 May 2020. Geographic testing disparities were evaluated with comparisons of the demographic makeup of zip codes around each testing site versus Monte Carlo simulations, aggregated to statewide and nationwide levels. State testing disparities were compared with statewide disparities in mortality observed one to 3 weeks later using multivariable regression, controlling for confounding disparities and characteristics. RESULTS: Nationwide, COVID-19 testing sites geographically overrepresented White residents on 7 May, underrepresented Hispanic residents on 16 April, 7 May and 28 May and overrepresented Black residents on 28 May compared with random distribution within counties, with new sites added over time exhibiting inconsistent disparities for Black and Hispanic populations. For every 1 percentage point increase in underrepresentation of Hispanic populations in zip codes with testing, mortality among the state's Hispanic population was 1.04 percentage points more over-representative (SE = 0.415, p = .01). CONCLUSIONS: American testing sites were not distributed equitably by race during this analysis, often underrepresenting minority populations who bear a disproportionate burden of COVID-19 cases and deaths. With an easy-to-implement measure of geographic disparity, these results provide empirical support for the consideration of access when distributing preventive resources.

Assessing mandatory stay-at-home and business closure effects on the spread of COVID-19.

BACKGROUND AND AIMS: The most restrictive nonpharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less-restrictive NPIs (lrNPIs). METHODS: We first estimate COVID-19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden and the United States. Using first-difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, 2 countries that did not implement mandatory stay-at-home and business closures, as comparison countries for the other 8 countries (16 total comparisons). RESULTS: Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a nonsignificant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, for example, the effect of mrNPIs was +7% (95% CI: -5%-19%) when compared with Sweden and + 13% (-12%-38%) when compared with South Korea (positive means pro-contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons. CONCLUSIONS: While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less-restrictive interventions.

Health outcomes and cost-effectiveness of treating depression in people with HIV in Sub-Saharan Africa: a model-based analysis.

High prevalence of depression among people living with HIV (PLHIV) impedes antiretroviral therapy (ART) adherence and viral suppression. We estimate the effectiveness and cost-effectiveness of strategies to treat depression among PLHIV in Sub-Saharan Africa (SSA). We developed a microsimulation model of HIV disease and care in Uganda which captured individuals' depression status and the relationship between depression and HIV behaviors. We consider a strategy of screening for depression and providing antidepressant therapy with fluoxetine at ART initiation or re-initiation (if a patient has dropped out). We estimate that over 10 years this strategy would reduce prevalence of depression among PLHIV by 16.0% [95% uncertainty bounds 15.8%, 16.1%] from a baseline prevalence of 28%, increase adherence to ART by 1.0% [1.0%, 1.0%], and decrease rates of loss to followup by 3.7% [3.4%, 4.1%]. This would decrease first-line ART failure rates by 2.5% [2.3%, 2.8%] and increase viral suppression rates by 1.0% [1.0%, 1.0%]. This strategy costs $15/QALY compared to the status quo, and was highly cost-effective over a broad range of sensitivity analyses. We conclude that screening for and treating depression among PLHIV in SSA with fluoxetine would be effective in improving HIV treatment outcomes and would be highly cost-effective.

Sustainable HIV treatment in Africa through viral-load-informed differentiated care.

There are inefficiencies in current approaches to monitoring patients on antiretroviral therapy in sub-Saharan Africa. Patients typically attend clinics every 1 to 3 months for clinical assessment. The clinic costs are comparable with the costs of the drugs themselves and CD4 counts are measured every 6 months, but patients are rarely switched to second-line therapies. To ensure sustainability of treatment programmes, a transition to more cost-effective delivery of antiretroviral therapy is needed. In contrast to the CD4 count, measurement of the level of HIV RNA in plasma (the viral load) provides a direct measure of the current treatment effect. Viral-load-informed differentiated care is a means of tailoring care so that those with suppressed viral load visit the clinic less frequently and attention is focussed on those with unsuppressed viral load to promote adherence and timely switching to a second-line regimen. The most feasible approach to measuring viral load in many countries is to collect dried blood spot samples for testing in regional laboratories; however, there have been concerns over the sensitivity and specificity of this approach to define treatment failure and the delay in returning results to the clinic. We use modelling to synthesize evidence and evaluate the cost-effectiveness of viral-load-informed differentiated care, accounting for limitations of dried blood sample testing. We find that viral-load-informed differentiated care using dried blood sample testing is cost-effective and is a recommended strategy for patient monitoring, although further empirical evidence as the approach is rolled out would be of value. We also explore the potential benefits of point-of-care viral load tests that may become available in the future.

Impact and cost-effectiveness of snail control to achieve disease control targets for schistosomiasis.

Schistosomiasis is a parasitic disease that affects over 240 million people globally. To improve population-level disease control, there is growing interest in adding chemical-based snail control interventions to interrupt the lifecycle of Schistosoma in its snail host to reduce parasite transmission. However, this approach is not widely implemented, and given environmental concerns, the optimal conditions for when snail control is appropriate are unclear. We assessed the potential impact and cost-effectiveness of various snail control strategies. We extended previously published dynamic, age-structured transmission and cost-effectiveness models to simulate mass drug administration (MDA) and focal snail control interventions against Schistosoma haematobium across a range of low-prevalence (5-20%) and high-prevalence (25-50%) rural Kenyan communities. We simulated strategies over a 10-year period of MDA targeting school children or entire communities, snail control, and combined strategies. We measured incremental cost-effectiveness in 2016 US dollars per disability-adjusted life year and defined a strategy as optimally cost-effective when maximizing health gains (averted disability-adjusted life years) with an incremental cost-effectiveness below a Kenya-specific economic threshold. In both low- and high-prevalence settings, community-wide MDA with additional snail control reduced total disability by an additional 40% compared with school-based MDA alone. The optimally cost-effective scenario included the addition of snail control to MDA in over 95% of simulations. These results support inclusion of snail control in global guidelines and national schistosomiasis control strategies for optimal disease control, especially in settings with high prevalence, "hot spots" of transmission, and noncompliance to MDA.

Drought and intimate partner violence towards women in 19 countries in sub-Saharan Africa during 2011-2018: A population-based study.

BACKGROUND: Drought has many known deleterious impacts on human health, but little is known about the relationship between drought and intimate partner violence (IPV). We aimed to evaluate this relationship and to assess effect heterogeneity between population subgroups among women in 19 sub-Saharan African countries. METHODS AND FINDINGS: We used data from 19 Demographic and Health Surveys from 2011 to 2018 including 83,990 partnered women aged 15-49 years. Deviations in rainfall in the year before the survey date were measured relative to the 29 previous years using Climate Hazards Group InfraRed Precipitation with Station data, with recent drought classified as ordinal categorical variable (severe: ≤10th percentile; mild/moderate: >10th percentile to ≤30th percentile; none: >30th percentile). We considered 4 IPV-related outcomes: reporting a controlling partner (a risk factor for IPV) and experiencing emotional violence, physical violence, or sexual violence in the 12 months prior to survey. Logistic regression was used to estimate marginal risk differences (RDs). We evaluated the presence of effect heterogeneity by age group and employment status. Of the 83,990 women included in the analytic sample, 10.7% (9,019) experienced severe drought and 23.4% (19,639) experienced mild/moderate drought in the year prior to the survey, with substantial heterogeneity across countries. The mean age of respondents was 30.8 years (standard deviation 8.2). The majority of women lived in rural areas (66.3%) and were married (73.3%), while less than half (42.6%) were literate. Women living in severe drought had higher risk of reporting a controlling partner (marginal RD in percentage points = 3.0, 95% CI 1.3, 4.6; p < 0.001), experiencing physical violence (marginal RD = 0.8, 95% CI 0.1, 1.5; p = 0.019), and experiencing sexual violence (marginal RD = 1.2, 95% CI 0.4, 2.0; p = 0.001) compared with women not experiencing drought. Women living in mild/moderate drought had higher risk of reporting physical (marginal RD = 0.7, 95% CI 0.2, 1.1; p = 0.003) and sexual violence (marginal RD = 0.7, 95% CI 0.3, 1.2; p = 0.001) compared with those not living in drought. We did not find evidence for an association between drought and emotional violence. In analyses stratified by country, we found 3 settings where drought was protective for at least 1 measure of IPV: Namibia, Tanzania, and Uganda. We found evidence for effect heterogeneity (additive interaction) for the association between drought and younger age and between drought and employment status, with stronger associations between drought and IPV among adolescent girls and unemployed women. This study is limited by its lack of measured hypothesized mediating variables linking drought and IPV, prohibiting a formal mediation analysis. Additional limitations include the potential for bias due to residual confounding and potential non-differential misclassification of the outcome measures leading to an attenuation of observed associations. CONCLUSIONS: Our findings indicate that drought was associated with measures of IPV towards women, with larger positive associations among adolescent girls and unemployed women. There was heterogeneity in these associations across countries. Weather shocks may exacerbate vulnerabilities among women in sub-Saharan Africa. Future work should further evaluate potential mechanisms driving these relationships.

Racial disparities in knowledge, attitudes and practices related to COVID-19 in the USA.

BACKGROUND: Recent reports indicate racial disparities in the rates of infection and mortality from the 2019 novel coronavirus (coronavirus disease 2019 [COVID-19]). The aim of this study was to determine whether disparities exist in the levels of knowledge, attitudes and practices (KAPs) related to COVID-19. METHODS: We analyzed data from 1216 adults in the March 2020 Kaiser Family Foundation 'Coronavirus Poll', to determine levels of KAPs across different groups. Univariate and multivariate regression analysis was used to identify predictors of KAPs. RESULTS: In contrast to White respondents, Non-White respondents were more likely to have low knowledge (58% versus 30%; P < 0.001) and low attitude scores (52% versus 27%; P < 0.001), but high practice scores (81% versus 59%; P < 0.001). By multivariate regression, White race (odds ratio [OR] 3.06; 95% confidence interval [CI]: 1.70-5.50), higher level of education (OR 1.80; 95% CI: 1.46-2.23) and higher income (OR 2.06; 95% CI: 1.58-2.70) were associated with high knowledge of COVID-19. Race, sex, education, income, health insurance status and political views were all associated with KAPs. CONCLUSIONS: Racial and socioeconomic disparity exists in the levels of KAPs related to COVID-19. More work is needed to identify educational tools that tailor to specific racial and socioeconomic groups.

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.

Age distribution, trends, and forecasts of under-5 mortality in 31 sub-Saharan African countries: A modeling study.

BACKGROUND: Despite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates. METHODS AND FINDINGS: Data came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee-Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries. CONCLUSIONS: To our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ≥ 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.