Explore the vast range of titles available.

Potential cost-effective barriers in cost-effectiveness studies mean that budgetary impact analyses should also be included in post-2015 Sustainable Development Goal projects says Joshua Salomon and colleagues.

Measurements of health indicators are rarely available for every population and period of interest, and available data may not be comparable. The Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) define best reporting practices for studies that calculate health estimates for multiple populations (in time or space) using multiple information sources. Health estimates that fall within the scope of GATHER include all quantitative population-level estimates (including global, regional, national, or subnational estimates) of health indicators, including indicators of health status, incidence and prevalence of diseases, injuries, and disability and functioning; and indicators of health determinants, including health behaviours and health exposures. GATHER comprises a checklist of 18 items that are essential for best reporting practice. A more detailed explanation and elaboration document, describing the interpretation and rationale of each reporting item along with examples of good reporting, is available on the GATHER website.

Healthy life expectancy (HALE) summarises mortality and non-fatal outcomes in a single measure of average population health. It has been used to compare health between countries, or to measure changes over time. These comparisons can inform policy questions that depend on how morbidity changes as mortality decreases. We characterise current HALE and changes over the past two decades in 187 countries. Using inputs from the Global Burden of Disease Study (GBD) 2010, we assessed HALE for 1990 and 2010. We calculated HALE with life table methods, incorporating estimates of average health over each age interval. Inputs from GBD 2010 included age-specific information for mortality rates and prevalence of 1160 sequelae, and disability weights associated with 220 distinct health states relating to these sequelae. We computed estimates of average overall health for each age group, adjusting for comorbidity with a Monte Carlo simulation method to capture how multiple morbidities can combine in an individual. We incorporated these estimates in the life table by the Sullivan method to produce HALE estimates for each population defined by sex, country, and year. We estimated the contributions of changes in child mortality, adult mortality, and disability to overall change in population health between 1990 and 2010. In 2010, global male HALE at birth was 59·0 years (uncertainty interval 57·3–60·6) and global female HALE at birth was 63·2 years (61·4–65·0). HALE increased more slowly than did life expectancy over the past 20 years, with each 1-year increase in life expectancy at birth associated with a 10-month increase in HALE. Across countries in 2010, male HALE at birth ranged from 27·8 years (17·2–36·5) in Haiti, to 70·6 years (68·6–72·2) in Japan. Female HALE at birth ranged from 37·1 years (26·8–43·8) in Haiti, to 75·5 years (73·3–77·3) in Japan. Between 1990 and 2010, male HALE increased by 5 years or more in 48 countries compared with 43 countries for female HALE, while male HALE decreased in 22 countries and 11 for female HALE. Between countries and over time, life expectancy was strongly and positively related to number of years lost to disability. This relation was consistent between sexes, in cross-sectional and longitudinal analysis, and when assessed at birth, or at age 50 years. Changes in disability had small effects on changes in HALE compared with changes in mortality. HALE differs substantially between countries. As life expectancy has increased, the number of healthy years lost to disability has also increased in most countries, consistent with the expansion of morbidity hypothesis, which has implications for health planning and health-care expenditure. Compared with substantial progress in reduction of mortality over the past two decades, relatively little progress has been made in reduction of the overall effect of non-fatal disease and injury on population health. HALE is an attractive indicator for monitoring health post-2015. The Bill & Melinda Gates Foundation

Unvaccinated persons without previous Covid-19 had the highest risk of omicron infection; those who had been infected after emergence of the delta variant and had received three mRNA vaccine doses were the most protected.

Patients with chronic hepatitis B infection (CHB) have an increased risk for death from liver cirrhosis and hepatocellular carcinoma (HCC). In the United States, only an estimated 37% of adults with chronic hepatitis B diagnosis without cirrhosis receive monitoring with at least an annual alanine transaminase (ALT) and hepatitis B deoxyribonucleic acid (DNA), and an estimated 59% receive antiviral treatment when they develop active hepatitis or cirrhosis. A Markov model was used to calculate the costs, health impact and cost-effectiveness of increased monitoring of adults with HBeAg negative inactive or HBeAg positive immune tolerant CHB who have no cirrhosis or significant fibrosis and are not recommended by the current American Association for the Study of Liver Diseases (AASLD) clinical practice guidelines to receive antiviral treatment, and to assess whether the addition of HCC surveillance would be cost-effective. For every 100,000 adults with CHB who were initially not recommended for treatment, if the monitoring rate increased from the current 37% to 90% and treatment rate increased from 59% to 80%, 4,600 cases of cirrhosis, 2,450 cases of HCC and 4,700 HBV-related deaths would be averted with a gain of 45,000 QALYs and a savings of$180 million in lifetime health care costs. At a willingness to pay threshold of $ 100,000/QALY, the addition of HCC surveillance with the standard recommended biannual liver ultrasound and alfa fetoprotein levels is likely cost-effective if the HCC risk ≥ 0.55%/year. Regular monitoring of persons with inactive or immune tolerant CHB who are initially not recommended to receive antiviral treatment in the United States is cost-saving. The addition of HCC surveillance with biannual US and AFP would be cost-effective for individuals with HCC incidence ≥ 0.55%/year.

The Xpert MTB/RIF test enables rapid detection of tuberculosis (TB) and rifampicin resistance. The World Health Organization recommends Xpert for initial diagnosis in individuals suspected of having multidrug-resistant TB (MDR-TB) or HIV-associated TB, and many countries are moving quickly toward adopting Xpert. As roll-out proceeds, it is essential to understand the potential health impact and cost-effectiveness of diagnostic strategies based on Xpert. We evaluated potential health and economic consequences of implementing Xpert in five southern African countries--Botswana, Lesotho, Namibia, South Africa, and Swaziland--where drug resistance and TB-HIV coinfection are prevalent. Using a calibrated, dynamic mathematical model, we compared the status quo diagnostic algorithm, emphasizing sputum smear, against an algorithm incorporating Xpert for initial diagnosis. Results were projected over 10- and 20-y time periods starting from 2012. Compared to status quo, implementation of Xpert would avert 132,000 (95% CI: 55,000-284,000) TB cases and 182,000 (97,000-302,000) TB deaths in southern Africa over the 10 y following introduction, and would reduce prevalence by 28% (14%-40%) by 2022, with more modest reductions in incidence. Health system costs are projected to increase substantially with Xpert, by US$460 million (294-699 million) over 10 y. Antiretroviral therapy for HIV represents a substantial fraction of these additional costs, because of improved survival in TB/HIV-infected populations through better TB case-finding and treatment. Costs for treating MDR-TB are also expected to rise significantly with Xpert scale-up. Relative to status quo, Xpert has an estimated cost-effectiveness of US$959 (633-1,485) per disability-adjusted life-year averted over 10 y. Across countries, cost-effectiveness ratios ranged from US$792 (482-1,785) in Swaziland to US$1,257 (767-2,276) in Botswana. Assessing outcomes over a 10-y period focuses on the near-term consequences of Xpert adoption, but the cost-effectiveness results are conservative, with cost-effectiveness ratios assessed over a 20-y time horizon approximately 20% lower than the 10-y values. Introduction of Xpert could substantially change TB morbidity and mortality through improved case-finding and treatment, with more limited impact on long-term transmission dynamics. Despite extant uncertainty about TB natural history and intervention impact in southern Africa, adoption of Xpert evidently offers reasonable value for its cost, based on conventional benchmarks for cost-effectiveness. However, the additional financial burden would be substantial, including significant increases in costs for treating HIV and MDR-TB. Given the fundamental influence of HIV on TB dynamics and intervention costs, care should be taken when interpreting the results of this analysis outside of settings with high HIV prevalence.

Additionally, differences in measurement methods mean that data might not be comparable over time or across populations. Because of these data gaps and measurement challenges, incomplete data together with statistical or mathematical models are often used to calculate estimates of health indicators. GATHER checklist of information that should be included in reports of global health estimates. http://dx.doi.org/10.1371/journal.pmed.1002056.t001 The GATHER working group and the responses to the online survey, both drawn from our networks of collaborators, were dominated by residents of high-income countries. GATHER also requires that authors report a quantitative measure of the uncertainty associated with global health estimates, such as uncertainty intervals. Global health estimates are usually affected by multiple sources of error, such as measurement error during data collection, inability to register all cases or obtain a truly random sample, errors in adjusting input data for sources of bias, and the use of a model to calculate estimates [26,27].

Tuberculosis transmission and progression are largely driven by social factors such as poor living conditions and poor nutrition. Increased standards of living and social approaches helped to decrease the burden of tuberculosis before the introduction of chemotherapy in the 1940s. Since then, management of tuberculosis has been largely biomedical. More funding for tuberculosis since 2000, coinciding with the Millennium Development Goals, has yielded progress in tuberculosis mortality but smaller reductions in incidence, which continues to pose a risk to sustainable development, especially in poor and susceptible populations. These at-risk populations need accelerated progress to end tuberculosis as resolved by the World Health Assembly in 2015. Effectively addressing the worldwide tuberculosis burden will need not only enhancement of biomedical approaches but also rebuilding of the social approaches of the past. To combine a biosocial approach, underpinned by social, economic, and environmental actions, with new treatments, new diagnostics, and universal health coverage, will need multisectoral coordination and action involving the health and other governmental sectors, as well as participation of the civil society, and especially the poor and susceptible populations. A biosocial approach to stopping tuberculosis will not only target morbidity and mortality from disease but would also contribute substantially to poverty alleviation and sustainable development that promises to meet the needs of the present, especially the poor, and provide them and subsequent generations an opportunity for a better future.

Estimating population sizes of adolescents who identify as lesbian, gay, or bisexual (LGB) is important for addressing health needs and disparities. Most states have Youth Risk Behavior Surveys (YRBS) among high school students, but not all include an item about sexual identity. This study's aim was to estimate the percentages of students identifying as LGB stratified by sex, age, and race and ethnicity where state data is incomplete. States where 2021 YRBS data are not available are outside the scope of this study. We developed two random forests trained separately for each sex and evaluated the models' performance in predicting percentages of respondents identifying as LGB by state and demographic strata. We then estimated percentages for states that did not include or have responses to the LGB identity question available in 2021. The random forests outperformed benchmark comparison models based on a simple logistic regression approach. Estimates of students who identify as LGB across demographic strata and states ranged 5%-30%. The estimated percentages for states that did not ask students about sexual identity fell within the same range. Our approach to deriving state-level estimates of LGB students by sex, race and ethnicity, and age performs well and can be used to inform efforts to improve health and well-being of LGB youth.

Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 404,214 COVID-19 deaths by the end of 2020, and that 28% of the US population had been infected. There was county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.