Quantifying changes in global health inequality: the Gini and Slope Inequality Indices applied to the Global Burden of Disease data, 1990-2017

Concentration of spending and share of specialty drug spending in Medicare Part D over a 10-year period

BACKGROUND

In 2021, Medicare Part D gross prescription drug spending amounted to $216 billion, a number that has more than doubled over the last 10 years. Spending in Medicare Part D is concentrated on a small number of drugs, and spending on specialty drugs has increased in recent years. However, the extent to which concentration in Part D spending has changed over time and the drivers of this change have not been described.

OBJECTIVE

To quantify the time trends in Medicare Part D spending and utilization, the concentration of spending, and the share of spending accounted for by specialty drugs from 2012 to 2021.

METHODS

In this repeated cross-sectional study, we used data from the Centers for Medicare & Medicaid Services Part D Drug Spending Dashboard to investigate the time trends in total gross spending, prescriptions claims, and the average cost of a prescription claim for Part D drugs. We assessed the concentration based on the share of total gross spending and prescriptions by the drugs with the top 1%, 5%, and 10% of the highest spending and Lorenz curves and Gini coefficients. In addition, we stratified our analyses by specialty and nonspecialty drugs.

RESULTS

Over the last 10 years, total gross drug spending in Medicare Part D increased by 103.5%, with a compounded annual growth rate of 8.2%. This change was driven by both increases in prescription claims and price increases of existing drugs to a similar degree. The concentration of spending intensified, with the top 1% of drugs accounting for an escalating share of total spending (from 31.4% to 41.1%). Over the 10-year study period, these top-spending drugs accounted for 5.6% of prescriptions but 34.6% of spending. Lorenz curves and increased Gini coefficients similarly showed that a smaller number of drugs accounted for increased spending over the study period. Specialty drug spending increased by 566.5%, with a compounded annual growth rate of 23.5%. The share of total spending on specialty drugs increased from 21.7% in 2012 to 71.1% in 2021. In 2021, specialty drugs accounted for 6.2% of prescriptions but 71.1% of total spending.

CONCLUSIONS

Medicare Part D gross drug spending became increasingly more concentrated from 2012 to 2021, which was especially pronounced for specialty drugs. Increases in prices for specialty and other brand-name drugs will likely continue to drive gross spending upward. Although the Inflation Reduction Act provisions will likely reduce net spending on selected drugs, other policy changes may be warranted.

National-wide survey of ophthalmic human resources in China in 2021

PURPOSE

To evaluate the availability of human resources for ophthalmic services in mainland China.

METHODS

In 2021, we conducted a nationwide survey of ophthalmic outpatient services across 2996 tertiary hospitals and 10,404 secondary hospitals in 31 provinces in mainland China.

RESULTS

The response rate was 73.6% (9856/13400), with 78.7% (7759/9856) providing ophthalmic services. By 2021, the total number of ophthalmologists, ophthalmic nurses, and optometrists was 48,652, 64,495, and 14,320, respectively. The densities (per 50,000 population) were 1.7, 2.25, and 0.47, respectively. The density of ophthalmologists was < 1 only in the XiZang region. The average doctor-patient ratio was 2584.8. In Shanghai and Zhejiang provinces, this ratio exceeded 4000.

CONCLUSION

There are currently 1.7 ophthalmologists, 2.25 nurses, and 0.47 optometrists for every 50,000 people in China. The number of ophthalmologists has reached the global average, but the number of optometrists is far below the global average. And the medical pressure across China is uneven, with some provinces such as Shanghai and Zhejiang facing enormous pressure.

Evolving trends, regional differences, determinants, and disease sources of provincial-level health inequalities in china 1990-2019: a temporal convergence and novel triple decomposition analysis

BACKGROUND

Promoting health equity has been a worldwide goal, but serious challenges remain globally and within China. Multiple decomposition of the sources and determinants of health inequalities has significant implications for narrowing health inequalities and improve health equity.

METHODS

Life expectancy (LE), healthy life expectancy (HALE), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life-year (DALY) rates in 31 provinces of mainland China were selected as health status indicators, obtained from the Global Burden of Disease (GBD) database. Temporal convergence analysis was used to test the evolving trends of health status. Dagum's Gini coefficient decomposition was used to decompose the overall Gini coefficient based on intraregional and interregional differences. Oaxaca-Blinder decomposition was used to calculate contributions of determinants to interregional differences. The factor-decomposed Gini coefficient was used to analyze the absolute and marginal contribution of each component to overall Gini coefficients.

RESULTS

From 1990-2019, China witnessed notable improvements in health status measured by LE, HALE, ASMR and age-standardized DALY rates.Nevertheless, the three regions (East, Central and West) exhibited significant inter-regional differences in health status, with the differences between the East and West being the largest. The adjusted short-term conditional β-convergence model indicated that the inter-provincial differences in LE, HALE, ASMR, and age-standardized DALY rates significantly converged at annual rates of 0.31%, 0.35%, 0.19%, and 0.28% over 30 years. The overall Gini coefficients of LE, HALE, and age-standardized DALY rates decreased, while the ASMR exhibited an opposite trend. Inter-regional and intra-regional differences accounted for >70% and <30% of overall Gini coefficients, respectively. Attribution analysis showed that socioeconomic determinants explained 85.77% to 91.93% of the eastern-western differences between 2010-2019, followed by health system determinants explaining 7.79% to 11.61%. The source-analysis of Gini coefficients of ASMR and age-standardized DALY rates revealed that noncommunicable diseases (NCDs) made the largest and increasing absolute contribution, while communicable, maternal, neonatal, and nutritional diseases (CMNNDs) had a diminishing and lower impact. However, NCDs exerted a negative marginal effect on the Gini coefficient, whereas CMNNDs exhibited a positive marginal effect, indicating that controlling CMNNDs may be more effective in reducing health inequities.

CONCLUSIONS

Regional differences are a major source of health inequities in China. Prioritizing prevention and control of CMNNDs, rather than NCDs, may yield more pronounced impacts on reducing health inequalities from the perspective of marginal effect, although NCDs remain the largest absolute contributor to health inequalities.

Equity in national healthcare economic evaluation guidelines: Essential or extraneous?

BACKGROUND

The focus on health maximisation in a healthcare economic evaluation (HEE) - that is health gains are of equal value regardless of the recipient- has significant implications as health systems attempt to address persistent and growing health inequities. This study aimed to systematically compare and contrast the equity principles of different health technology assessment (HTA) agencies and how equity is addressed in HEE guidelines.

METHODS

HTA agencies were identified through the ISPOR, GEAR, iDSI, HTAi, INAHTA, HTAsiaLink, and RedETSA websites in June 2021 and updated in August 2023. Agencies websites were then searched to retrieve HEE guidelines. The guidelines were grouped into two categories: well-established and newly-developed agency guidelines, based on whether or not they published their first guidelines before 2009. Data extracted summarised the methodological details in the reference cases, including specifics on how equity featured and in what role. In those agencies where equity did not feature explicitly in the HEE guidelines, an additional search of the agency website was undertaken to understand if equity featured in those agencies' decision-making frameworks.

RESULTS

The study included 46 guidelines from 51 countries. Only 30% of the guidelines were explicit about the equity assumptions. Health equity (using a broad definition) was mentioned in 29 guidelines and 14 included a specific definition while only seven recommended specific methods to incorporate inequalities. Addressing equity concerns was usually suggested as an additional analyses rather than a key part of the assessment. It was unclear how equity was incorporated into decision-making processes. In addition, equity was mentioned in other guidance - such as decision-making frameworks - provided by five agencies that did not mention it in the HEE guidelines, and 7 of 14 topic selection criteria that were identified.

CONCLUSION

Equity is given less attention than efficiency in HEE guidelines. This indicates that HTA agencies while subscribing to an extra-welfarist approach have a narrow evaluative space - focusing on maximising health and not considering the opportunity cost of the equity constraint. The omission of equity and the lack of systematic approaches in guidelines poses a threat to the international endeavours to reduce inequities. It is timely for HTA agencies to reconsider their positions on equity explicitly.

The global burden, trends and cross-country inequalities of female breast and gynaecologic cancers: A population based study

OBJECTIVE

To analyse the global burden, trends and cross-country inequalities of female breast and gynaecologic cancers (FeBGCs).

DESIGN

Population-Based Study.

SETTING

Data sourced from the Global Burden of Disease Study 2019.

POPULATION

Individuals diagnosed with FeBGCs.

METHODS

Age-standardised mortality rates (ASMRs), age-standardised Disability-Adjusted Life Years (DALYs) rates (ASDRs) and their 95% uncertainty interval (UI) described the burden. Estimated annual percentage changes (EAPCs) and their confidence interval (CI) of age-standardised rates (ASRs) illustrated trends. Social inequalities were quantified using the Slope Index of Inequality (SII) and Concentration Index.

MAIN OUTCOME MEASURES

The main outcome measures were the burden of FeBGCs and the trends in its inequalities over time.

RESULTS

In 2019, the ASDRs per 100 000 females were as follows: breast cancer: 473.83 (95% UI: 437.30-510.51), cervical cancer: 210.64 (95% UI: 177.67-234.85), ovarian cancer: 124.68 (95% UI: 109.13-138.67) and uterine cancer: 210.64 (95% UI: 177.67-234.85). The trends per year from 1990 to 2019 were expressed as EAPCs of ASDRs and these: for Breast cancer: -0.51 (95% CI: -0.57 to -0.45); Cervical cancer: -0.95 (95% CI: -0.99 to -0.89); Ovarian cancer: -0.08 (95% CI: -0.12 to -0.04); and Uterine cancer: -0.84 (95% CI: -0.93 to -0.75). In the Social Inequalities Analysis (1990-2019) the SII changed from 689.26 to 607.08 for Breast, from -226.66 to -239.92 for cervical, from 222.45 to 228.83 for ovarian and from 74.61 to 103.58 for uterine cancer. The concentration index values ranged from 0.2 to 0.4.

CONCLUSIONS

The burden of FeBGCs worldwide showed a downward trend from 1990 to 2019. Countries or regions with higher Socio-demographic Index (SDI) bear a higher DALYs burden of breast, ovarian and uterine cancers, while those with lower SDI bear a heavier burden of cervical cancer. These inequalities increased over time.

Examining geographical inequalities for malaria outcomes and spending on malaria in 40 malaria-endemic countries, 2010-2020

BACKGROUND

While substantial gains have been made in the fight against malaria over the past 20 years, malaria morbidity and mortality are marked by inequality. The equitable elimination of malaria within countries will be determined in part by greater spending on malaria interventions, and how those investments are allocated. This study aims to identify potential drivers of malaria outcome inequality and to demonstrate how spending through different mechanisms might lead to greater health equity.

METHODS

Using the Gini index, subnational estimates of malaria incidence and mortality rates from 2010 to 2020 were used to quantify the degree of inequality in malaria burden within countries with incidence rates above 5000 cases per 100,000 people in 2020. Estimates of Gini indices represent within-country distributions of disease burden, with high values corresponding to inequitable distributions of malaria burden within a country. Time series analyses were used to quantify associations of malaria inequality with malaria spending, controlling for country socioeconomic and population characteristics.

RESULTS

Between 2010 and 2020, varying levels of inequality in malaria burden within malaria-endemic countries was found. In 2020, values of the Gini index ranged from 0.06 to 0.73 for incidence, 0.07 to 0.73 for mortality, and 0.00 to 0.36 for case fatality. Greater total malaria spending, spending on health systems strengthening for malaria, healthcare access and quality, and national malaria incidence were associated with reductions in malaria outcomes inequality within countries. In addition, government expenditure on malaria, aggregated government and donor spending on treatment, and maternal educational attainment were also associated with changes in malaria outcome inequality among countries with the greatest malaria burden.

CONCLUSIONS

The findings from this study suggest that prioritizing health systems strengthening in malaria spending and malaria spending in general especially from governments will help to reduce inequality of the malaria burden within countries. Given heterogeneity in outcomes in countries currently fighting to control malaria, and the challenges in increasing both domestic and international funding allocated to control and eliminate malaria, the efficient targeting of limited resources is critical to attain global malaria eradication goals.

Subnational inequalities in years of life lost and associations with socioeconomic factors in pre-pandemic Europe, 2009-19: an ecological study

BACKGROUND

Health inequalities have been associated with shorter lifespans. We aimed to investigate subnational geographical inequalities in all-cause years of life lost (YLLs) and the association between YLLs and socioeconomic factors, such as household income, risk of poverty, and educational attainment, in countries within the European Economic Area (EEA) before the COVID-19 pandemic.

METHODS

In this ecological study, we extracted demographic and socioeconomic data from Eurostat for 1390 small regions and 285 basic regions for 32 countries in the EEA, which was complemented by a time-trend analysis of subnational regions within the EEA. Age-standardised YLL rates per 100 000 population were estimated from 2009 to 2019 based on methods from the Global Burden of Disease study. Geographical inequalities were assessed using the Gini coefficient and slope index of inequality. Socioeconomic inequalities were assessed by investigating the association between socioeconomic factors (educational attainment, household income, and risk of poverty) and YLLs in 2019 using negative binomial mixed models.

FINDINGS

Between Jan 1, 2009, and Dec 31, 2019, YLLs lowered in almost all subnational regions. The Gini coefficient of YLLs across all EEA regions was 14·2% (95% CI 13·6-14·8) for females and 17·0% (16·3 to 17·7) for males. Relative geographical inequalities in YLLs among women were highest in the UK (Gini coefficient 11·2% [95% CI 10·1-12·3]) and among men were highest in Belgium (10·8% [9·3-12·2]). The highest YLLs were observed in subnational regions with the lowest levels of educational attainment (incident rate ratio [IRR] 1·19 [1·13-1·26] for females; 1·22 [1·16-1·28] for males), household income (1·35 [95% CI 1·19-1·53]), and the highest poverty risk (1·25 [1·18-1·34]).

INTERPRETATION

Differences in YLLs remain within, and between, EEA countries and are associated with socioeconomic factors. This evidence can assist stakeholders in addressing health inequities to improve overall disease burden within the EEA.

FUNDING

Research Council of Norway; Development, and Innovation Fund of Hungary; Norwegian Institute of Public Medicine; and COST Action 18218 European Burden of Disease Network.

Causal Assessment of Income Inequality on Self-Rated Health and All-Cause Mortality: A Systematic Review and Meta-Analysis

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level.

CONTEXT

Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal.

METHODS

We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints.

FINDINGS

The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility.

CONCLUSIONS

Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches.

Contributions of declining mortality, overall and from HIV, TB and malaria, to reduced health inequality and inequity across countries

The objective to reduce global health inequalities and inequities is integral to the global development agenda, from the Universal Declaration of Human Rights to the sustainable development goals and the ongoing response to coronavirus disease. Yet, summary measures of global health gains or of the cost-effectiveness of global health programmes barely capture how well they improve the lives of the most disadvantaged populations. This paper instead explores the distribution of global health gains across countries and the implications for health inequality and inequity (here referring to health disadvantages that reinforce economic disadvantage, and vice versa) across countries. Specifically, it studies the distribution of gains in life expectancy across countries (overall and owing to reduced mortality from HIV, TB and malaria), using the Gini index and a concentration index ranking countries by gross domestic product (GDP) per capita as indicators of health inequality and inequity. By these counts, global inequality in life expectancy across countries declined by one-third between 2002 and 2019. Reduced mortality from HIV, TB and malaria accounted for one-half of this decline. Fifteen countries in sub-Saharan Africa, containing 5% of the global population, accounted for 40% of the global decline in inequality, with nearly six-tenth of this contribution coming from HIV, TB and malaria. Inequity in life expectancy across countries declined by nearly 37%, with a contribution from HIV, TB and malaria of 39% of this gain. Our findings show how simple indicators on the distribution of health gains across countries usefully complement aggregate measures of global health gains and underscore their positive contribution to the global development agenda.

Inequalities in the burden of non-communicable diseases across European countries: a systematic analysis of the Global Burden of Disease 2019 study

BACKGROUND

Although overall health status in the last decades improved, health inequalities due to non-communicable diseases (NCDs) persist between and within European countries. There is a lack of studies giving insights into health inequalities related to NCDs in the European Economic Area (EEA) countries. Therefore, the aim of the present study was to quantify health inequalities in age-standardized disability adjusted life years (DALY) rates for NCDs overall and 12 specific NCDs across 30 EEA countries between 1990 and 2019. Also, this study aimed to determine trends in health inequalities and to identify those NCDs where the inequalities were the highest.

METHODS

DALY rate ratios were calculated to determine and compare inequalities between the 30 EEA countries, by sex, and across time. Annual rate of change was used to determine the differences in DALY rate between 1990 and 2019 for males and females. The Gini Coefficient (GC) was used to measure the DALY rate inequalities across countries, and the Slope Index of Inequality (SII) to estimate the average absolute difference in DALY rate across countries.

RESULTS

Between 1990 and 2019, there was an overall declining trend in DALY rate, with larger declines among females compared to males. Among EEA countries, in 2019 the highest NCD DALY rate for both sexes were observed for Bulgaria. For the whole period, the highest DALY rate ratios were identified for digestive diseases, diabetes and kidney diseases, substance use disorders, cardiovascular diseases (CVD), and chronic respiratory diseases - representing the highest inequality between countries. In 2019, the highest DALY rate ratio was found between Bulgaria and Iceland for males. GC and SII indicated that the highest inequalities were due to CVD for most of the study period - however, overall levels of inequality were low.

CONCLUSIONS

The inequality in level 1 NCDs DALYs rate is relatively low among all the countries. CVDs, digestive diseases, diabetes and kidney diseases, substance use disorders, and chronic respiratory diseases are the NCDs that exhibit higher levels of inequality across countries in the EEA. This might be mitigated by applying tailored preventive measures and enabling healthcare access.

Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials

BACKGROUND

Individualized prediction of treatment response may improve the value proposition of advanced treatment options in severe asthma. This study aimed to investigate the combined capacity of patient characteristics in predicting treatment response to mepolizumab in patients with severe asthma.

METHODS

Patient-level data were pooled from two multinational phase 3 trials of mepolizumab in severe eosinophilic asthma. We fitted penalized regression models to quantify reductions in the rate of severe exacerbations and the 5-item Asthma Control Questionnaire (ACQ5) score. The capacity of 15 covariates towards predicting treatment response was quantified by the Gini index (measuring disparities in treatment benefit) as well as observed treatment benefit within the quintiles of predicted treatment benefit.

RESULTS

There was marked variability in the ability of patient characteristics to predict treatment response; covariates explained greater heterogeneity in predicting treatment response to asthma control than to exacerbation frequency (Gini index 0.35 v. 0.24). Key predictors for treatment benefit for severe exacerbations included exacerbation history, blood eosinophil count, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of nasal polyps. Overall, the average reduction in exacerbations was 0.90/year (95%CI, 0.87‒0.92) and average reduction in ACQ5 score was 0.18 (95% CI, 0.02‒0.35). Among the top 20% of patients for predicted treatment benefit, exacerbations were reduced by 2.23/year (95% CI, 2.03‒2.43) and ACQ5 score were reduced by 0.59 (95% CI, 0.19‒0.98). Among the bottom 20% of patients for predicted treatment benefit, exacerbations were reduced by 0.25/year (95% CI, 0.16‒0.34) and ACQ5 by -0.20 (95% CI, -0.51 to 0.11).

CONCLUSION

A precision medicine approach based on multiple patient characteristics can guide biologic therapy in severe asthma, especially in identifying patients who will not benefit as much from therapy. Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation.

TRIAL REGISTRATION

ClinicalTrials.gov number, NCT01691521 (registered September 24, 2012) and NCT01000506 (registered October 23, 2009).

Unemployment and expenditure on health and education as mediators of the association between toothbrushing and global income inequalities

Objective

The study assessed the association of country-level income inequalities with the percentage of schoolchildren toothbrushing-at-least-twice-daily; and the mediating effect of country-level unemployment rate and governmental expenditure on health and education (EH&E).

Methods

This was an ecological study. The dependent variable was country-level toothbrushing-at-least-twice-daily among 11-15-year-old schoolchildren. Data for the period 2009 to 2019 were extracted from two global surveys about schoolchildren’s health and from manuscripts identified through a systematic search of three databases. The independent variable was country-level income inequalities measured by the Gini coefficient (GC) extracted from the Sustainable Development Report 2021. The mediators were the unemployment rate and EH&E. We stratified the sample by the level of GC and assessed the correlation between the dependent and independent variables in each stratum. Linear regression was used to assess the relations between the dependent and independent variables, and mediation path analysis was used to quantify the direct, indirect, and total effects.

Results

Data were available for 127 countries. The mean (SD) percentage of children who brushed-at-least-twice-daily was 67.3 (16.1), the mean (SD) GC = 41.4 (8.2), unemployment rate = 7.5 (4.7) and EH&E = 8.4 (3.3). The percentage of children brushing at-least-twice-daily had weak and non-significant correlation with GC that was positive in countries with the least inequality and negative for countries with higher levels of inequality. A greater percentage of schoolchildren brushing-at-least-twice-daily was significantly associated with higher GC (B = 0.76, 95%CI: 0.33, 1.18), greater EH&E (B = 1.67, 95%CI: 0.69, 2.64) and lower unemployment rate (B=-1.03, 95%CI: -1.71, -0.35). GC had a significant direct positive effect (B = 0.76, 95%CI: 0.33, 1.18), a significant indirect negative effect through unemployment and EH&E (B=-0.47, 95%CI: -0.79, -0.24) and a non-significant total positive effect (B = 0.29, 95%CI: -0.09, 0.67) on the percentage of schoolchildren brushing-at-least-twice-daily.

Conclusion

Unemployment and EH&E mediated the association between income inequality and toothbrushing. Country-level factors may indirectly impact toothbrushing.

Global burden of atrial fibrillation/flutter due to high systolic blood pressure from 1990 to 2019: estimates from the global burden of disease study 2019

Atrial fibrillation/atrial flutter (AF/AFL) has progressed to be a public health concern, and high systolic blood pressure (HSBP) remains the leading risk factor for AF/AFL. This study estimated the HSBP attributable AF/AFL burden based on the data from the Global Burden of Disease (GBD) study 2019. Numbers, age-standardized rates (ASR) of deaths, disability-adjusted life years (DALYs), and corresponding estimated annual percentage change (EAPC) were analyzed by age, sex, sociodemographic index (SDI), and locations. Gini coefficient was calculated to evaluate health inequality. Globally, HSBP-related AF/AFL caused 107 091 deaths and 3 337 876 DALYs in 2019, an increase of 142.5% and 105.9% from 1990, respectively. The corresponding mortality and DALYs ASR declined by 5.8% and 7.7%. High-income Asia Pacific experienced the greatest decrease in mortality and DALYs ASR, whereas the largest increase was observed in Andean Latin America. Almost half of the HSBP-related AF/AFL burden was carried by high and high-middle SDI regions, and it was experiencing a shift to lower SDI regions. A negative correlation was detected between EAPC and SDI. Females and elderly people tended to have a higher AF/AFL burden, whereas young adults (30-49 years old) experienced an annual increase in AF/AFL burden. The Gini index of DALYs rate decreased from 0.224 in 1990 to 0.183 in 2019. Despite improved inequality having been observed over the past decades, the HSBP-related AF/AFL burden varied across regions, sexes, and ages. Cost-effective preventive, diagnostic, and therapeutic tools are required to be implemented in less developed regions.

Quantifying spatial heterogeneity of malaria in the endemic Papua region of Indonesia: Analysis of epidemiological surveillance data

Background

As control efforts progress towards elimination, malaria is likely to become more spatially concentrated in few local areas. The purpose of this study was to quantify and characterise spatial heterogeneity in malaria transmission-intensity across highly endemic Indonesian Papua.

Methods

We analysed individual-level malaria surveillance data for nearly half a million cases (2019-2020) reported in the Papua and West Papua provinces and adapted the Gini index approach to quantify spatial heterogeneity at the district and health-unit levels. In this context, high Gini index implies disproportionately distributed malaria cases across the region. We showed malaria incidence trends and the spatial and temporal distribution of sociodemographic characteristics and aetiological parasites among cases.

Findings

While Papua province accounted for the majority of malaria cases reported in the region and had seen a rise in transmission since 2015, West Papua province had maintained a comparatively low incidence. We observed that Gini index estimates were high, particularly when the lower spatial scale of health units was evaluated. The Gini index appears to be inversely associated to annual parasite-incidence, as well as the proportions of vivax malaria, male sex, and adults.

Interpretation

This study suggests that areas with varying levels of transmission-intensities exhibited distinct characteristics. Malaria was distributed in a markedly disproportionate manner throughout the region, emphasising the need for spatially targeted interventions. Periodic quantification and characterisation of risk heterogeneity at various spatial levels using routine malaria surveillance data may aid in tracking progress towards elimination and guiding evidence-informed prioritisation of resource allocation.

Funding

The study was funded by the Australian Government Department of Foreign Affairs and Trade Indo-Pacific Centre for Health Security through the Strengthening Preparedness in the Asia-Pacific Region through Knowledge (SPARK) project.

Using Microsimulation Modeling to Inform EHE Implementation Strategies in Los Angeles County

BACKGROUND

Pre-exposure prophylaxis (PrEP) is essential to ending HIV. Yet, uptake remains uneven across racial and ethnic groups. We aimed to estimate the impacts of alternative PrEP implementation strategies in Los Angeles County.

SETTING

Men who have sex with men, residing in Los Angeles County.

METHODS

We developed a microsimulation model of HIV transmission, with inputs from key local stakeholders. With this model, we estimated the 15-year (2021-2035) health and racial and ethnic equity impacts of 3 PrEP implementation strategies involving coverage with 9000 additional PrEP units annually, above the Status-quo coverage level. Strategies included PrEP allocation equally (strategy 1), proportionally to HIV prevalence (strategy 2), and proportionally to HIV diagnosis rates (strategy 3), across racial and ethnic groups. We measured the degree of relative equalities in the distribution of the health impacts using the Gini index (G) which ranges from 0 (perfect equality, with all individuals across all groups receiving equal health benefits) to 1 (total inequality).

RESULTS

HIV prevalence was 21.3% in 2021 [Black (BMSM), 31.1%; Latino (LMSM), 18.3%, and White (WMSM), 20.7%] with relatively equal to reasonable distribution across groups (G, 0.28; 95% confidence interval [CI], 0.26 to 0.34). During 2021-2035, cumulative incident infections were highest under Status-quo (n = 24,584) and lowest under strategy 3 (n = 22,080). Status-quo infection risk declined over time among all groups but remained higher in 2035 for BMSM (incidence rate ratio, 4.76; 95% CI: 4.58 to 4.95), and LMSM (incidence rate ratio, 1.74; 95% CI: 1.69 to 1.80), with the health benefits equally to reasonably distributed across groups (G, 0.32; 95% CI: 0.28 to 0.35). Relative to Status-quo, all other strategies reduced BMSM-WMSM and BMSM-LMSM disparities, but none reduced LMSM-WMSM disparities by 2035. Compared to Status-quo, strategy 3 reduced the most both incident infections (% infections averted: overall, 10.2%; BMSM, 32.4%; LMSM, 3.8%; WMSM, 3.5%) and HIV racial inequalities (G reduction, 0.08; 95% CI: 0.02 to 0.14).

CONCLUSIONS

Microsimulation models developed with early, continuous stakeholder engagement and inputs yield powerful tools to guide policy implementation.

Desigualdad en mortalidad estratificada según la densidad del recurso humano en 32 países americanos

Objetivos Medir desigualdades en salud mediante 12 indicadores de mortalidad, utilizando la densidad de recurso humano de profesionales de medicina (PMED) y enfermería (PENF) como estratificador de equidad en 32 países americanos. Métodos A partir de 12 indicadores de mortalidad, estratificados mediante densidad de PMED y PENF, se calculan tasas ponderadas, diferencias, correlación, indicadores simples y complejos de desigualdad. Resultados De 12 indicadores, 9 presentan mayor tasa en baja densidad de ambas profesiones y 7 presentan diferencias significativas. Hay alta variabilidad en brechas relativas (8,7 a 1,2); concentración desigual con afectación de grupos vulnerables; y mayor índice de la pendiente en mortalidad: materna, enfermedades transmisibles y diabetes.

The Gini coefficient as a useful measure of malaria inequality among populations

Background

Understanding inequality in infectious disease burden requires clear and unbiased indicators. The Gini coefficient, conventionally used as a macroeconomic descriptor of inequality, is potentially useful to quantify epidemiological heterogeneity. With a potential range from 0 (all populations equal) to 1 (populations having maximal differences), this coefficient is used here to show the extent and persistence of inequality of malaria infection burden at a wide variety of population levels.

Methods

First, the Gini coefficient was applied to quantify variation among World Health Organization world regions for malaria and other major global health problems. Malaria heterogeneity was then measured among countries within the geographical sub-region where burden is greatest, among the major administrative divisions in several of these countries, and among selected local communities. Data were analysed from previous research studies, national surveys, and global reports, and Gini coefficients were calculated together with confidence intervals using bootstrap resampling methods.

Results

Malaria showed a very high level of inequality among the world regions (Gini coefficient, G = 0.77, 95% CI 0.66–0.81), more extreme than for any of the other major global health problems compared at this level. Within the most highly endemic geographical sub-region, there was substantial inequality in estimated malaria incidence among countries of West Africa, which did not decrease between 2010 (G = 0.28, 95% CI 0.19–0.36) and 2018 (G = 0.31, 0.22–0.39). There was a high level of sub-national variation in prevalence among states within Nigeria (G = 0.30, 95% CI 0.26–0.35), contrasting with more moderate variation within Ghana (G = 0.18, 95% CI 0.12–0.25) and Sierra Leone (G = 0.17, 95% CI 0.12–0.22). There was also significant inequality in prevalence among local village communities, generally more marked during dry seasons when there was lower mean prevalence. The Gini coefficient correlated strongly with the standard coefficient of variation, which has no finite range.

Conclusions

The Gini coefficient is a useful descriptor of epidemiological inequality at all population levels, with confidence intervals and interpretable bounds. Wider use of the coefficient would give broader understanding of malaria heterogeneity revealed by multiple types of studies, surveys and reports, providing more accessible insight from available data.

Systematic analysis of the scientific literature on population surveillance

Introduction

Population surveillance provides data on the health status of the population through continuous scrutiny of different indicators. Identifying risk factors is essential for the quickly detecting and controlling of epidemic outbreaks and reducing the incidence of cross-infections and non-communicable diseases. The objective of the present study is to analyze research on population surveillance, identifying the main topics of interest for investigators in the area.

Methodology

We included documents indexed in the Web of Science Core Collection in the period from 2000 to 2019 and assigned with the generic Medical Subject Heading (MeSH) “population surveillance” or its related terms (“public health surveillance,” “sentinel surveillance” or “biosurveillance”). A co-occurrence analysis was undertaken to identify the document clusters comprising the main research topics. Scientific production, collaboration, and citation patterns in each of the clusters were characterized bibliometrically. We also analyzed research on coronaviruses, relating the results obtained to the management of the COVID-19 pandemic.

Results

We included 39,184 documents, which reflected a steady growth in scientific output driven by papers on “Public, Environmental & Occupational Health” (21.62% of the documents) and “Infectious Diseases” (10.49%). Research activity was concentrated in North America (36.41%) and Europe (32.09%). The USA led research in the area (40.14% of documents). Ten topic clusters were identified, including “Disease Outbreaks,” which is closely related to two other clusters (“Genetics” and “Influenza”). Other clusters of note were “Cross Infections” as well as one that brought together general public health concepts and topics related to non-communicable diseases (cardiovascular and coronary diseases, mental diseases, diabetes, wound and injuries, stroke, and asthma). The rest of the clusters addressed “Neoplasms,” “HIV,” “Pregnancy,” “Substance Abuse/Obesity,” and “Tuberculosis.” Although research on coronavirus has focused on population surveillance only occasionally, some papers have analyzed and collated guidelines whose relevance to the dissemination and management of the COVID-19 pandemic has become obvious. Topics include tracing the spread of the virus, limiting mass gatherings that would facilitate its propagation, and the imposition of quarantines. There were important differences in the scientific production and citation of different clusters: the documents on mental illnesses, stroke, substance abuse/obesity, and cross-infections had much higher citations than the clusters on disease outbreaks, tuberculosis, and especially coronavirus, where these values are substantially lower.

Conclusions

The role of population surveillance should be strengthened, promoting research and the development of public health surveillance systems in countries whose contribution to the area is limited.