Modeled estimates of HIV-serodifferent couples in tuberculosis-affected households in four sub-Saharan African countries.

Household-based tuberculosis (TB) contact evaluation may be an efficient strategy to reach people who could benefit from oral pre-exposure prophylaxis (PrEP) because of the epidemiological links between HIV and TB. This study estimated the number of HIV serodifferent couples in TB-affected households and potential HIV acquisitions averted through their PrEP use in 4 TB-HIV high-burden countries. We conducted a model-based analysis set in Ethiopia, Kenya, South Africa, and Uganda using parameters from population-based household surveys, systematic literature review and meta-analyses, and estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. We parameterized the nonlinear relationship between the proportion of serodifferent couples among people living with HIV and population-level HIV prevalence using Markov chain Monte Carlo methods. We integrated all parameters in a mathematical model and propagated uncertainty using a Monte Carlo approach. We estimated the HIV prevalence among adults aged 15-49 living in TB-affected households to be higher than in the general population in all 4 countries. The proportion of serodifferent couples among all couples in TB-affected households was also higher than in the general population (South Africa: 20.7% vs. 15.7%, Kenya: 15.7% vs. 5.7%, Uganda: 14.5% vs. 6.0%, Ethiopia: 4.1% vs. 0.8%). We estimated that up to 1,799 (95% UI: 1,256-2,341) HIV acquisitions in South Africa could be prevented annually by PrEP use in serodifferent couples in TB-affected households, 918 (95% UI: 409-1,450) in Kenya, 686 (95% UI: 505-871) in Uganda, and 408 (95% UI: 298-522) in Ethiopia. As couples in TB-affected households are more likely to be serodifferent than couples in the general population, offering PrEP during household TB contact evaluation may prevent a substantial number of HIV acquisitions.

Prevalence of Diabetic Retinopathy in the US in 2021.

Importance: Diabetic retinopathy (DR) is a common microvascular complication of diabetes and a leading cause of blindness among working-age adults in the US. Objective: To update estimates of DR and vision-threatening diabetic retinopathy (VTDR) prevalence by demographic factors and US county and state. Data Sources: The study team included data from the National Health and Nutrition Examination Survey (2005 to 2008 and 2017 to March 2020), Medicare fee-for-service claims (2018), IBM MarketScan commercial insurance claims (2016), population-based studies of adult eye disease (2001 to 2016), 2 studies of diabetes in youth (2021 and 2023), and a previously published analysis of diabetes by county (2012). The study team used population estimates from the US Census Bureau. Study Selection: The study team included relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System. Data Extraction and Synthesis: Using bayesian meta-regression methods, the study team estimated the prevalence of DR and VTDR stratified by age, a nondifferentiated sex and gender measure, race, ethnicity, and US county and state. Main Outcomes and Measures: The study team defined individuals with diabetes as those who had a hemoglobin A1c level at 6.5% or more, took insulin, or reported ever having been told by a physician or health care professional that they have diabetes. The study team defined DR as any retinopathy in the presence of diabetes, including nonproliferative retinopathy (mild, moderate, or severe), proliferative retinopathy, or macular edema. The study team defined VTDR as having, in the presence of diabetes, severe nonproliferative retinopathy, proliferative retinopathy, panretinal photocoagulation scars, or macular edema. Results: This study used data from nationally representative and local population-based studies that represent the populations in which they were conducted. For 2021, the study team estimated 9.60 million people (95% uncertainty interval [UI], 7.90-11.55) living with DR, corresponding to a prevalence rate of 26.43% (95% UI, 21.95-31.60) among people with diabetes. The study team estimated 1.84 million people (95% UI, 1.41-2.40) living with VTDR, corresponding to a prevalence rate of 5.06% (95% UI, 3.90-6.57) among people with diabetes. Prevalence of DR and VTDR varied by demographic characteristics and geography. Conclusions and Relevance: US prevalence of diabetes-related eye disease remains high. These updated estimates on the burden and geographic distribution of diabetes-related eye disease can be used to inform the allocation of public health resources and interventions to communities and populations at highest risk.

Frequency of HIV serodifferent couples within TB-affected households in a setting with a high burden of HIV-associated TB.

INTRODUCTION: Strong epidemiological links between human immunodeficiency virus (HIV) and tuberculosis (TB) may make household TB contact investigation an efficient strategy for HIV screening and finding individuals in serodifferent partnerships at risk of HIV and linking them to HIV prevention services. We aimed to compare the proportions of HIV serodifferent couples in TB-affected households and in the general population of Kampala, Uganda. METHODS: We included data from a cross-sectional trial of HIV counselling and testing (HCT) in the context of home-based TB evaluation in Kampala, Uganda in 2016-2017. After obtaining consent, community health workers visited the homes of participants with TB to screen contacts for TB and offer HCT to household members ≥ 15 years. We defined index participants and their spouses or parents as couples. Couples were classified as serodifferent if confirmed by self-reported HIV status or by HIV testing results. We used a two-sample test of proportions to compare the frequency of HIV serodifference among couples in the study to its prevalence among couples in Kampala in the 2011 Uganda AIDS Indicator Survey (UAIS). RESULTS: We included 323 index TB participants and 507 household contacts aged ≥ 18 years. Most index participants (55%) were male, while most (68%) adult contacts were female. There was ≥ 1 couple in 115/323 (35.6%) households, with most couples (98/115, 85.2%) including the index participant and spouse. The proportion of households with HIV-serodifferent couples was 18/323 (5.6%), giving a number-needed-to-screen of 18 households. The proportion of HIV serodifference among couples identified in the trial was significantly higher than among couples in the UAIS (15.7% vs. 8%, p = 0.039). The 18 serodifferent couples included 14 (77.8%) where the index participant was living with HIV and the spouse was HIV-negative, and 4 (22.2%) where the index partner was HIV-negative, while the spouse was living with HIV. CONCLUSIONS: The frequency of HIV serodifference among couples identified in TB-affected households was higher than in the general population. TB household contact investigation may be an efficient strategy for identifying people with substantial exposure to HIV and linking them to HIV prevention services.

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis.

BACKGROUND: The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes. METHODS: Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05. FINDINGS: Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures. INTERPRETATION: COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises. FUNDING: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Stakeholder perspectives on factors influencing acute care patient outcomes: A qualitative approach to model refinement.

Background: Health systems have long been interested in the best practices for staffing in the acute care setting. Studies on staffing often focus on registered nurses and nurse-to-patient staffing ratios. There are fewer studies on the relationship between interprofessional team members or contextual factors such as hospital and community characteristics and patient outcomes. This qualitative study aimed to refine a causal model by soliciting hospital stakeholder feedback on staffing and patient outcomes. Methods: We conducted a qualitative study using semi-structured interviews and thematic analysis to understand hospital stakeholder perspectives and their experiences of factors that affect acute care inpatient outcomes. Interviews were conducted in 2022 with 38 hospital stakeholders representing 19 hospitals across Washington State. Results: Findings support a model of characteristics impacting patient outcomes to include the complex and interconnected relationships between community, hospital, patient, and staffing characteristics. Within the model, patient characteristics are nested into hospital characteristics, and in turn these were nested within community characteristics to highlight the importance of setting and context when evaluating outcomes. Together, these factors influenced both staff characteristics and patient outcomes, while these two categories also share a direct relationship. Conclusion: Findings can be applied to hospitals and health systems across the globe to examine how external factors such as community resource availability impact care delivery. Future research should expand on this work with specific attention to how staffing changes and interprofessional team composition can improve patient outcomes.

Prevalence of Age-Related Macular Degeneration in the US in 2019.

Importance: Age-related macular degeneration (AMD) is a leading cause of vision loss and blindness. AMD prevalence has not been estimated for the US in over a decade and early-stage AMD prevalence estimates are scarce and inconsistently measured. Objective: To produce estimates of early- and late-stage AMD prevalence overall and by age, gender, race and ethnicity, county, and state. Design, Setting, and Participants: The study team conducted a bayesian meta-regression analysis of relevant data sources containing information on the prevalence of AMD among different population groups in the US. Data Sources: We included data from the American Community Survey (2019), the National Health and Nutrition Examination Survey (2005-2008), US Centers for Medicare & Medicaid Services claims for fee-for-service beneficiaries (2018), and population-based studies (2004-2016). Study Selection: We included all relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System. Data Extraction and Synthesis: The prevalence of early- and late-stage AMD was estimated and stratified when possible by factors including county, age group, gender, and race and ethnicity. Data analysis occurred from June 2021 to April 2022. Main Outcomes or Measures: The prevalence of early- (defined as retinal pigment epithelium abnormalities or the presence of drusen 125 or more microns in diameter in either eye) and late-stage (defined as choroidal neovascularization and/or geographic atrophy in either eye) manifestations of AMD. Results: This study used data from nationally representative and local population-based studies that represent the populations in which they were conducted. For 2019, we estimated that there were 18.34 million people 40 years and older (95% uncertainty interval [UI], 15.30-22.03) living with early-stage AMD, corresponding to a crude prevalence rate of 11.64% (95% UI, 9.71-13.98). We estimated there were 1.49 million people 40 years and older (95% UI, 0.97-2.15) living with late-stage AMD, corresponding to a crude prevalence rate of 0.94% (95% UI, 0.62-1.36). Prevalence rates of early- and late-stage AMD varied by demographic characteristics and geography. Conclusions and Relevance: We estimated a higher prevalence of early-stage AMD and a similar prevalence of late-stage AMD as compared with earlier studies. State-level and county-level AMD estimates may help guide public health practice.

Estimated Health Outcomes and Costs of COVID-19 Prophylaxis With Monoclonal Antibodies Among Unvaccinated Household Contacts in the US.

Importance: The COVID-19 pandemic has led to more than 900 000 deaths in the US and continues to disrupt lives even as effective vaccines are available. Objective: To estimate the health outcomes and net cost of implementing postexposure prophylaxis (PEP) with monoclonal antibodies (mAbs) against household exposure to COVID-19. Design, Setting, and Participants: This study is a decision analytical model of results from a randomized clinical trial of casirivimab with imdevimab administered as subcutaneous injections to unvaccinated, SARS-CoV-2-negative household contacts of people with confirmed COVID-19 with complementary data on household demographic structure, vaccine coverage, and confirmed COVID-19 case counts. The study used US data from May 2021 for a simulated population of US individuals of all ages within low-transmission or high-transmission scenarios. Exposures: Age, sex, race, ethnicity, and COVID-19 vaccination status. Main Outcome or Measures: Symptomatic infection, hospitalization, death, and net payer cost of monoclonal antibody PEP for COVID-19. Results: In a month of transmission intensity similar to that of May 2021, a mAb PEP program reaching 50% of exposed, unvaccinated household members aged 50 years and older was estimated to avert 1820 symptomatic infections (95% uncertainty interval [UI], 1220-2454 symptomatic infections), 528 hospitalizations (95% UI, 354-724 hospitalizations), and 84 deaths (95% UI, 55-116 deaths) in a low-transmission scenario and 4834 symptomatic infections (95% UI, 3375-6257 symptomatic infections), 1404 hospitalizations (95% UI, 974-1827 hospitalizations), and 223 deaths (95% UI, 152-299 deaths) in a high-transmission scenario. Without mAb PEP, the estimated cost of hospitalizations due to COVID-19 infections from household exposure in the lower transmission scenario was $149 million (95% UI, $115-$196 million), whereas the estimated hospitalization cost in the higher transmission scenario was $400 million (95% UI, $312-$508 million). In the lower transmission scenario, mAb PEP administered to 50% of eligible contacts aged 80 years and older was estimated to have 82% probability of saving costs, but was not associated with cost savings at age thresholds of 50 years and older or 20 years and older. In contrast, in the high-transmission scenario, mAb PEP administered to 50% of eligible household contacts had estimated cost savings in 100% of simulations at the 80-year age threshold, 96% of simulations at the 50-year threshold, and 2% of simulations at the 20-year thresholds. Conclusions and Relevance: In this modeling study of a simulated US population, a mAb PEP for COVID-19 program was estimated to improve health outcomes and reduce costs. In the setting of a susceptible variant of SARS-CoV-2, health system and public health actors would have an opportunity to improve health and reduce net payer costs through COVID-19 PEP with mAbs.

Cost-effectiveness of antenatal multiple micronutrients and balanced energy protein supplementation compared to iron and folic acid supplementation in India, Pakistan, Mali, and Tanzania: A dynamic microsimulation study.

BACKGROUND: Malnutrition among women of childbearing age is especially prevalent in Asia and sub-Saharan Africa and can be harmful to the fetus during pregnancy. In the most recently available Demographic and Health Survey (DHS), approximately 10% to 20% of pregnant women in India, Pakistan, Mali, and Tanzania were undernourished (body mass index [BMI] <18.5 kg/m2), and according to the Global Burden of Disease (GBD) 2017 study, approximately 20% of babies were born with low birth weight (LBW; <2,500 g) in India, Pakistan, and Mali and 8% in Tanzania. Supplementing pregnant women with micro and macronutrients during the antenatal period can improve birth outcomes. Recently, the World Health Organization (WHO) recommended antenatal multiple micronutrient supplementation (MMS) that includes iron and folic acid (IFA) in the context of rigorous research. Additionally, WHO recommends balanced energy protein (BEP) for undernourished populations. However, few studies have compared the cost-effectiveness of different supplementation regimens. We compared the cost-effectiveness of MMS and BEP with IFA to quantify their benefits in 4 countries with considerable prevalence of maternal undernutrition. METHODS AND FINDINGS: Using nationally representative estimates from the 2017 GBD study, we conducted an individual-based dynamic microsimulation of population cohorts from birth to 2 years of age in India, Pakistan, Mali, and Tanzania. We modeled the effect of maternal nutritional supplementation on infant birth weight, stunting and wasting using effect sizes from Cochrane systematic reviews and published literature. We used a payer's perspective and obtained costs of supplementation per pregnancy from the published literature. We compared disability-adjusted life years (DALYs) and incremental cost-effectiveness ratios (ICERs) in a baseline scenario with existing antenatal IFA coverage with scenarios where 90% of antenatal care (ANC) attendees receive either universal MMS, universal BEP, or MMS + targeted BEP (women with prepregnancy BMI <18.5 kg/m2 receive BEP containing MMS while women with BMI ≥18.5 kg/m2 receive MMS). We obtained 95% uncertainty intervals (UIs) for all outputs to represent parameter and stochastic uncertainty across 100 iterations of model runs. ICERs for all scenarios were lowest in Pakistan and greatest in Tanzania, in line with the baseline trend in prevalence of and attributable burden to LBW. MMS + targeted BEP averts more DALYs than universal MMS alone while remaining cost-effective. ICERs for universal MMS compared to baseline IFA were $52 (95% UI: $28 to $78) for Pakistan, $72 (95% UI: $37 to $118) for Mali, $70 (95% UI: $43 to $104) for India, and $253 (95% UI: $112 to $481) for Tanzania. ICERs for MMS + targeted BEP compared to baseline IFA were $54 (95% UI: $32 to $77) for Pakistan, $73 (95% UI: $40 to $104) for Mali, $83 (95% UI: $58 to $111) for India, and $245 (95% UI: $127 to $405) for Tanzania. Study limitations include generalizing experimental findings from the literature to our populations of interest and using population-level input parameters that may not reflect the heterogeneity of subpopulations. Additionally, our microsimulation fuses multiple sources of data and may be limited by data quality and availability. CONCLUSIONS: In this study, we observed that MMS + targeted BEP averts more DALYs and remains cost-effective compared to universal MMS. As countries consider using MMS in alignment with recent WHO guidelines, offering targeted BEP is a cost-effective strategy that can be considered concurrently to maximize benefits and synergize program implementation.

Estimating the population at high risk for tuberculosis through household exposure in high-incidence countries: a model-based analysis.

BACKGROUND: Household contacts of people with pulmonary tuberculosis (TB) have greater risk of developing TB. Recent guidelines conditionally recommended TB preventive treatment (TPT) for household contacts of any age living in TB high-incidence countries, expanding earlier guidance to provide TPT to household contacts under five. The all-age population of household contacts has not been estimated. METHODS: Our model-based estimation included 20 countries with >80% of incident TB globally in 2019. We developed country-specific distributions of household composition by age and sex using bootstrap resampling from health surveys and census data. We incorporated age-, sex-, year-, and location-specific estimates of pulmonary TB incidence from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 to estimate the population in each country sharing a household with someone with incident pulmonary TB, and quantified uncertainty using a Monte Carlo approach. FINDINGS: We estimate that 38 million [95% uncertainty interval (UI) 33- 43 million] individuals lived in a household with someone with incident pulmonary TB in 2019 in these 20 countries. Children under five made up 12% of the population with household exposure, while adults were 65%. Zimbabwe, Mozambique, Zambia, and Pakistan had the highest proportion of the population with household exposure, while India had the highest number of contacts (11·4 million, 95% UI 9·7-13·4 million). INTERPRETATION: Expanding TPT evaluation to household contacts of all ages in high-incidence countries could include a population more than 7-times larger than the under-5 contacts previously prioritized. This would substantially increase the impact of household contact investigation on reducing TB morbidity and mortality. FUNDING: JMR is supported by the National Institute of Allergy and Infectious Diseases (K01 AI138620). This research was funded in part by a 2020 developmental grant from the University of Washington / Fred Hutch Center for AIDS Research, an NIH funded program under award number AI027757 which is supported by the following NIH Institutes and Centers: NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, NIA, NIGMS, NIDDK. This work was funded in part by the National Science Foundation (DMS-1839116).

Improving methods to measure comparable mortality cause (IMMCMC) gold standard verbal autopsy dataset.

OBJECTIVES: Gold standard cause of death data is critically important to improve verbal autopsy (VA) methods in diagnosing cause of death where civil and vital registration systems are inadequate or poor. As part of a three-country research study-Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study-data were collected on clinicopathological criteria-based gold standard cause of death from hospital record reviews with matched VAs. The purpose of this data note is to make accessible a de-identified format of these gold standard VAs for interested researchers to improve the diagnostic accuracy of VA methods. DATA DESCRIPTION: The study was conducted between 2011 and 2014 in the Philippines, Bangladesh, and Papua New Guinea. Gold standard diagnoses of underlying causes of death for deaths occurring in hospital were matched to VAs conducted using a standardized VA questionnaire developed by the Population Health Metrics Consortium. 3512 deaths were collected in total, comprised of 2491 adults (12 years and older), 320 children (28 days to 12 years), and 702 neonates (0-27 days).

Conflict-related intentional injuries in Baghdad, Iraq, 2003-2014: A modeling study and proposed method for calculating burden of injury in conflict.

BACKGROUND: Previous research has focused on the mortality associated with armed conflict as the primary measure of the population health effects of war. However, mortality only demonstrates part of the burden placed on a population by conflict. Injuries and resultant disabilities also have long-term effects on a population and are not accounted for in estimates that focus solely on mortality. Our aim was to demonstrate a new method to describe the effects of both lives lost, and years of disability generated by a given conflict, with data from the US-led 2003 invasion and subsequent occupation of Iraq. METHODS AND FINDINGS: Our data come from interviews conducted in 2014 in 900 Baghdad households containing 5,148 persons. The average household size was 5.72 persons. The majority of the population (55.8%) were between the ages of 19 and 60. Household composition was evenly divided between males and females. Household sample collection was based on methodology previously designed for surveying households in war zones. Survey questions were answered by the head of household or senior adult present. The questions included year the injury occurred, the mechanism of injury, the body parts injured, whether injury resulted in disability and, if so, the length of disability. We present this modeling study to offer an innovative methodology for measuring "years lived with disability" (YLDs) and "years of life lost" (YLLs) attributable to conflict-related intentional injuries, using the Global Burden of Disease (GBD) approach. YLDs were calculated with disability weights, and YLLs were calculated by comparing the age at death to the GBD standard life table to calculate remaining life expectancy. Calculations were also performed using Iraq-specific life expectancy for comparison. We calculated a burden of injury of 5.6 million disability-adjusted life years (DALYs) lost due to conflict-related injuries in Baghdad from 2003 to 2014. The majority of DALYs lost were attributable to YLLs, rather than YLDs, 4.99 million YLLs lost (95% uncertainty interval (UI) 3.87 million to 6.13 million) versus 616,000 YLDs lost (95% UI 399,000 to 894,000). Cause-based analysis demonstrated that more DALYs were lost to due to gunshot wounds (57%) than any other cause. Our study has several limitations. Recall bias regarding the reporting and attribution of injuries is possible. Second, we have no data past the time of the interview, so we assumed individuals with ongoing disability at the end of data collection would not recover, possibly counting more disability for injuries occurring later. Additionally, incomplete data could have led to misclassification of deaths, resulting in an underestimation of the total burden of injury. CONCLUSIONS: In this study, we propose a methodology to perform burden of disease calculations for conflict-related injuries (expressed in DALYs) in Baghdad from 2003 to 2014. We go beyond previous reports of simple mortality to assess long-term population health effects of conflict-related intentional injuries. Ongoing disability is, in cross section, a relatively small 10% of the total burden. Yet, this small proportion creates years of demands on the health system, persistent limitations in earning capacity, and continuing burdens of care provision on family members.

Factors associated with delays in the search for care in under-5 deaths in Yucatán, Mexico / Factores asociados con demoras en la búsqueda de atención en muertes de menores de cinco años en Yucatán, México

Abstract: Objective: We examined delays during the search for care and associations with mother, child, or health services characteristics, and with symptoms reported prior to death. Materials and methods: Cross-sectional study comprising household interviews with 252 caregivers of children under-5 who died in the state of Yucatán, Mexico, during 2015-2016. We evaluated the three main delays: 1) time to identify symptoms and start search for care, 2) transport time to health facility, and 3) wait time at health facility. Results: Children faced important delays including a mean time to start the search for care of 4.1 days. The mean transport time to the first facility was longer for children enrolled in Seguro Popular and there were longer wait times at public facilities, especially among children who also experienced longer travel time Conclusions: Providing resources to enable caregivers to access health services in a timely manner may reduce delays in seeking care.

Resumen: Objetivo: Analizar las demoras en la búsqueda de atención y su asociación con características de la madre, del niño y los servicios de salud, así como con los síntomas reportados antes de la defunción. Material y métodos: Diseño transversal con entrevistas a 252 cuidadores que se encargaron de niños menores de cinco años que fallecieron en el estado de Yucatán, México, durante 2015-2016. Se evaluaron tres demoras: 1) tiempo en identificar la complicación e iniciar el proceso de búsqueda; 2) tiempo de transporte; y 3) tiempo de espera en la unidad de salud. Resultados: Los niños enfrentaron demoras importantes en la búsqueda de atención. La media de tiempo para iniciar la búsqueda de atención fue de 4.1 días. La media de tiempo de transporte a la primera unidad de atención fue mayor para niños inscritos en el Seguro Popular y hubo tiempos de espera más largos en unidades de salud del sector público, especialmente entre niños que tuvieron tiempos de transporte largos. Conclusión: Proporcionar recursos que permitan a los cuidadores acceder a los servicios de salud de manera oportuna puede reducir las demoras en la búsqueda de atención.

Factors associated with delays in the search for care in under-5 deaths in Yucatán, Mexico.

OBJECTIVE: We examined delays during the search for care and associations with mother, child, or health services characteristics, and with symptoms reported prior to death. MATERIALS AND METHODS: Cross-sectional study compris-ing household interviews with 252 caregivers of children under-5 who died in the state of Yucatán, Mexico, during 2015-2016. We evaluated the three main delays: 1) time to identify symptoms and start search for care, 2) transport time to health facility, and 3) wait time at health facility. RESULTS: Children faced important delays including a mean time to start the search for care of 4.1 days. The mean transport time to the first facility was longer for children enrolled in Seguro Popular and there were longer wait times at public facilities, especially among children who also experienced longer travel time. CONCLUSIONS: Providing resources to enable caregiv-ers to access health services in a timely manner may reduce delays in seeking care.

Prevalence of Visual Acuity Loss or Blindness in the US: A Bayesian Meta-analysis.

IMPORTANCE: Globally, more than 250 million people live with visual acuity loss or blindness, and people in the US fear losing vision more than memory, hearing, or speech. But it appears there are no recent empirical estimates of visual acuity loss or blindness for the US. OBJECTIVE: To produce estimates of visual acuity loss and blindness by age, sex, race/ethnicity, and US state. DATA SOURCES: Data from the American Community Survey (2017), National Health and Nutrition Examination Survey (1999-2008), and National Survey of Children's Health (2017), as well as population-based studies (2000-2013), were included. STUDY SELECTION: All relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System were included. DATA EXTRACTION AND SYNTHESIS: The prevalence of visual acuity loss or blindness was estimated, stratified when possible by factors including US state, age group, sex, race/ethnicity, and community-dwelling or group-quarters status. Data analysis occurred from March 2018 to March 2020. MAIN OUTCOMES OR MEASURES: The prevalence of visual acuity loss (defined as a best-corrected visual acuity greater than or equal to 0.3 logMAR) and blindness (defined as a logMAR of 1.0 or greater) in the better-seeing eye. RESULTS: For 2017, this meta-analysis generated an estimated US prevalence of 7.08 (95% uncertainty interval, 6.32-7.89) million people living with visual acuity loss, of whom 1.08 (95% uncertainty interval, 0.82-1.30) million people were living with blindness. Of this, 1.62 (95% uncertainty interval, 1.32-1.92) million persons with visual acuity loss are younger than 40 years, and 141 000 (95% uncertainty interval, 95 000-187 000) persons with blindness are younger than 40 years. CONCLUSIONS AND RELEVANCE: This analysis of all available data with modern methods produced estimates substantially higher than those previously published.

Understanding data use and preference of data visualization for public health professionals: A qualitative study.

OBJECTIVE: This study aimed to assess public health professionals' use of data, information, and evidence and to understand perceptions and preferences regarding data visualization to inform future design of data visualization tools. DESIGN: We conducted qualitative interviews with public health professionals who use data for decision making as part of community health assessment and program planning from state and local health departments across six states. RESULTS: We identified four themes: 1) collection of data, information, and evidence; 2) management and analysis of data and information to inform decisions; 3) use of data to support public health practice; and 4) preferences for data visualization and how visualization is being used. Public health professionals use data, information, and evidence from various resources for communicating with co-workers, stakeholders, and the public, and decision making regarding their programs and services. CONCLUSION: Data visualization tools can help public health professionals improve their understanding and communication, their education of stakeholders, and their decision making using data, information, and evidence. Public health professionals believe in the value of using data, information, and evidence. Opportunities exist in ways to support public health professionals' data use by adopting data visualization tools and by mitigating systematic challenges in public health information systems.

Ensemble modelling in descriptive epidemiology: burden of disease estimation.

Ensemble modelling is a quantitative method that combines information from multiple individual models and has shown great promise in statistical machine learning. Ensemble models have a theoretical claim to being models that make the 'best' predictions possible. Applications of ensemble models to health research have included applying ensemble models like the super learner and random forests to epidemiological prediction tasks. Recently, ensemble methods have been applied successfully in burden of disease estimation. This article aims to provide epidemiologists with a practical understanding of the mechanisms of an ensemble model and insight into constructing ensemble models that are grounded in the epidemiological dynamics of the prediction problem of interest. We summarize the history of ensemble models, present a user-friendly framework for conceptualizing and constructing ensemble models, walk the reader through a tutorial of applying the framework to an application in burden of disease estimation, and discuss further applications.

Association Between Subnational Vaccine Coverage, Migration, and Incident Cases of Measles, Mumps, and Rubella in Iraq, 2001-2016.

OBJECTIVE: This analysis examines governorate-level disease incidence as well as the relationship between incidence and the number of persons of concern for three vaccine-preventable diseases-measles, mumps, and rubella-between 2001 and 2016. METHODS: Using Iraqi Ministry of Health and United Nations High Commissioner for Refugees (UNHCR) data, we performed descriptive analyses of disease incidence and conducted a pooled statistical analysis with a linear mixed effects regression model to examine the role of vaccine coverage and migration of persons of concern on subnational disease incidence. RESULTS: We found large variability in governorate-level incidence, particularly for measles (on the order of 100x). We identified decreases in incident measles cases per 100,000 persons for each additional percent vaccinated (0.82, 95% CI: [0.64, 1.00], p-value < 0.001) and for every additional 10,000 persons of concern when incorporating displacement into our model (0.26, 95% CI: [0.22, 0.30], p-value < 0.001). These relationships were insignificant for mumps and rubella. CONCLUSIONS: National level summary statistics do not adequately capture the high geospatial disparity in disease incidence between 2001 and 2016. This variability is complicated by MMR vaccine coverage and the migration of "persons of concern" (refugees) during conflict. We found that even when vaccine coverage was constant, measles incidence was higher in locations with more displaced persons, suggesting conflict fueled the epidemic in ways that vaccine coverage could not control.

Born to fail: flaws in replication design produce intended results.

We recently published in BMC Medicine an evaluation of the comparative diagnostic performance of InSilicoVA, a software to map the underlying causes of death from verbal autopsy interviews. The developers of this software claim to have failed to replicate our results and appear to have also failed to locate our replication archive for this work. In this Correspondence, we provide feedback on how this might have been done more usefully and offer some suggestions to improve future attempts at reproducible research. We also offer an alternative interpretation of the results presented by Li et al., namely that, out of 100 verbal autopsy interviews, InSilicoVA will, at best, correctly identify the underlying cause of death in 40 cases and incorrectly in 60 - a markedly inferior performance to alternative existing approaches.