Exploring the "Urban Advantage" in Access to Immunization Services: A Comparison of Zero-Dose Prevalence Between Rural, and Poor and Non-poor Urban Households Across 97 Low- and Middle-Income Countries

Urban children are more likely to be vaccinated than rural children, but that advantage is not evenly distributed. Children living in poor urban areas face unique challenges, living far from health facilities and with lower-quality health services, which can impact their access to life-saving vaccines. Our goal was to compare the prevalence of zero-dose children in poor and non-poor urban and rural areas of low- and middle-income countries (LMICs). Zero-dose children were those who failed to receive any dose of a diphtheria-pertussis-tetanus (DPT) containing vaccine. We used data from nationally representative household surveys of 97 LMICs to investigate 201,283 children aged 12-23 months. The pooled prevalence of zero-dose children was 6.5% among the urban non-poor, 12.6% for the urban poor, and 14.7% for the rural areas. There were significant differences between these areas in 43 countries. In most of these countries, the non-poor urban children were at an advantage compared to the urban poor, who were still better off or similar to rural children. Our results emphasize the inequalities between urban and rural areas, but also within urban areas, highlighting the challenges faced by poor urban and rural children. Outreach programs and community interventions that can reach poor urban and rural communities-along with strengthening of current vaccination programs and services-are important steps to reduce inequalities and ensure that no child is left unvaccinated.

Child immunization status according to number of siblings and birth order in 85 low- and middle-income countries: a cross-sectional study

Background

Identification of unvaccinated children is important for preventing deaths due to infections. Number of siblings and birth order have been postulated as risk factors for zero-dose prevalence.

Methods

We analysed nationally representative cross-sectional surveys from 85 low and middle-income countries (2010-2020) with information on immunisation status of children aged 12-35 months. Zero-dose prevalence was defined as the failure to receive any doses of DPT (diphtheria-pertussis-tetanus) vaccine. We examined associations with birth order and the number of siblings, adjusting for child's sex, maternal age and education, household wealth quintiles and place of residence. Poisson regression was used to calculate zero-dose prevalence ratios.

Findings

We studied 375,548 children, of whom 13.7% (n = 51,450) were classified as zero-dose. Prevalence increased monotonically with birth order and with the number of siblings, with prevalence increasing from 11.0% for firstborn children to 17.1% for birth order 5 or higher, and from 10.5% for children with no siblings to 17.2% for those with four or more siblings. Adjustment for confounders attenuated but did not eliminate these associations. The number of siblings remained as a strong risk factor when adjusted for confounders and birth order, but the reverse was not observed. Among children with the same number of siblings, there was no clear pattern in zero-dose prevalence by birth order; for instance, among children with two siblings, the prevalence was 13.0%, 14.7%, and 13.3% for firstborn, second, and third-born, respectively. Similar results were observed for girls and boys. 9513 families had two children aged 12-35 months. When the younger sibling was unvaccinated, 61.9% of the older siblings were also unvaccinated. On the other hand, when the younger sibling was vaccinated, only 5.9% of the older siblings were unvaccinated.

Interpretation

The number of siblings is a better predictor than birth order in identifying children to be targeted by immunization campaigns. Zero-dose children tend to be clustered within families.

Funding

Gavi, the Vaccine Alliance.

Religious affiliation as a driver of immunization coverage: Analyses of zero-dose vaccine prevalence in 66 low- and middle-income countries

Background

The literature on the association between religion and immunization coverage is scant, mostly consisting of single-country studies. Analyses in low and middle-income countries (LMICs) to assess whether the proportions of zero-dose children vary according to religion remains necessary to better understand non-socioeconomic immunization barriers and to inform interventions that target zero-dose children.

Methods

We included 66 LMICs with standardized national surveys carried out since 2010, with information on religion and vaccination. The proportion of children who failed to receive any doses of a diphtheria-pertussis-tetanus (DPT) containing vaccine - a proxy for no access to routine vaccination or "zero-dose" status - was the outcome. Differences among religious groups were assessed using a test for heterogeneity. Additional analyses were performed controlling for the fixed effect of country, household wealth, maternal education, and urban-rural residence to assess associations between religion and immunization.

Findings

In 27 countries there was significant heterogeneity in no-DPT prevalence according to religion. Pooled analyses adjusted for wealth, maternal education, and area of residence showed that Muslim children had 76% higher no-DPT prevalence than Christian children. Children from the majority religion in each country tended to have lower no-DPT prevalence than the rest of the population except in Muslim-majority countries.

Interpretation

Analyses of gaps in coverage according to religion are relevant to renewing efforts to reach groups that are being left behind, with an important role in the reduction of zero-dose children.

Ethnic disparities in immunisation: analyses of zero-dose prevalence in 64 countries

BACKGROUND

The Sustainable Development Goals (SDGs) recommend stratification of health indicators by ethnic group, yet there are few studies that have assessed if there are ethnic disparities in childhood immunisation in low-income and middle-income countries (LMICs).

METHODS

We identified 64 LMICs with standardised national surveys carried out since 2010, which provided information on ethnicity or a proxy variable and on vaccine coverage; 339 ethnic groups were identified after excluding those with fewer than 50 children in the sample and countries with a single ethnic group. Lack of vaccination with diphtheria-pertussis-tetanus vaccine-a proxy for no access to routine vaccination or 'zero-dose' status-was the outcome of interest. Differences among ethnic groups were assessed using a χ2 test for heterogeneity. Additional analyses controlled for household wealth, maternal education and urban-rural residence.

FINDINGS

The median gap between the highest and lowest zero-dose prevalence ethnic groups in all countries was equal to 10 percentage points (pp) (IQR 4-22), and the median ratio was 3.3 (IQR 1.8-6.7). In 35 of the 64 countries, there was significant heterogeneity in zero-dose prevalence among the ethnic groups. In most countries, adjustment for wealth, education and residence made little difference to the ethnic gaps, but in four countries (Angola, Benin, Nigeria and Philippines), the high-low ethnic gap decreased by over 15 pp after adjustment. Children belonging to a majority group had 29% lower prevalence of zero-dose compared with the rest of the sample.

INTERPRETATION

Statistically significant ethnic disparities in child immunisation were present in over half of the countries studied. Such inequalities have been seldom described in the published literature. Regular analyses of ethnic disparities are essential for monitoring trends, targeting resources and assessing the impact of health interventions to ensure zero-dose children are not left behind in the SDG era.

Economic-Related Inequalities in Zero-Dose Children: A Study of Non-Receipt of Diphtheria-Tetanus-Pertussis Immunization Using Household Health Survey Data from 89 Low- and Middle-Income Countries

Despite advances in scaling up new vaccines in low- and middle-income countries, the global number of unvaccinated children has remained high over the past decade. We used 2000–2019 household survey data from 154 surveys representing 89 low- and middle-income countries to assess within-country, economic-related inequality in the prevalence of one-year-old children with zero doses of diphtheria–tetanus–pertussis (DTP) vaccine. Zero-dose DTP prevalence data were disaggregated by household wealth quintile. Difference, ratio, slope index of inequality, concentration index, and excess change measures were calculated to assess the latest situation and change over time, by country income grouping for 17 countries with high zero-dose DTP numbers and prevalence. Across 89 countries, the median prevalence of zero-dose DTP was 7.6%. Within-country inequalities mostly favored the richest quintile, with 19 of 89 countries reporting a rich–poor gap of ≥20.0 percentage points. Low-income countries had higher inequality than lower–middle-income countries and upper–middle-income countries (difference between the median prevalence in the poorest and richest quintiles: 14.4, 8.9, and 2.7 percentage points, respectively). Zero-dose DTP prevalence among the poorest households of low-income countries declined between 2000 and 2009 and between 2010 and 2019, yet economic-related inequality remained high in many countries. Widespread economic-related inequalities in zero-dose DTP prevalence are particularly pronounced in low-income countries and have remained high over the previous decade.

Children of more empowered women are less likely to be left without vaccination in low- and middle-income countries: A global analysis of 50 DHS surveys

Background

To help provide a global understanding of the role of gender-related barriers to vaccination, we have used a broad measure of women’s empowerment and explored its association with the prevalence of zero-dose children aged 12-23 months across many low- and middle-income countries, using data from standardized national household surveys.

Methods

We used data from Demographic and Health Surveys (DHS) of 50 countries with information on both women’s empowerment and child immunisation. Zero-dose was operationally defined as the proportion of children who failed to receive any doses of the diphtheria, pertussis, and tetanus containing vaccines (DPT). We measured women’s empowerment using the SWPER Global, an individual-level indicator estimated for women aged 15-49 years who are married or in union and with three domains: social independence, decision-making and attitude towards violence. We estimated two summary measures of inequality, the slope index of inequality (SII) and the concentration index (CIX). Results were presented for individual and pooled countries.

Results

In the country-level (ecological) analyses we found that the higher the proportion of women with high empowerment, the lower the zero-dose prevalence. In the individual level analyses, overall, children with highly-empowered mothers presented lower prevalence of zero-dose than those with less-empowered mothers. The social independence domain presented more consistent associations with zero-dose. In 42 countries, the lowest zero-dose prevalence was found in the high empowerment groups, with the slope index of inequality showing significant results in 28 countries. When we pooled all countries using a multilevel Poisson model, children from mothers in the low and medium levels of the social independence domain had respectively 3.3 (95% confidence interval (CI) = 2.3, 4.7) and 1.8 (95% CI = 1.5, 2.1) times higher prevalence of zero-dose compared to those in the high level.

Conclusions

Our country-level and individual-level analyses support the importance of women’s empowerment for child vaccination, especially in countries with weaker routine immunisation programs.

Assessing the overlap between immunisation and other essential health interventions in 92 low- and middle-income countries using household surveys: opportunities for expanding immunisation and primary health care

BACKGROUND

Unvaccinated children may live in households with limited access to other primary health care (PHC) services, and routine vaccination services may provide the opportunity to bring caregivers into contact with the health system. We aimed to investigate the overlap between not being vaccinated and failing to receive other PHC services in low- and middle-income countries (LMICs).

METHODS

Using Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) data between 2010-2019 from 92 LMICs, we analysed six vaccination indicators based on the bacille Calmette-Guérin (BCG), polio, diphtheria-pertussis-tetanus (DPT) and measles vaccines and their overlap with four other PHC indicators - at least four antenatal care (ANC) visits, institutional delivery, careseeking for common childhood illnesses or symptoms and place for handwashing in the home - in 211,141 children aged 12-23 months. Analyses were stratified according to wealth quintiles and World Bank income levels.

FINDINGS

Unvaccinated children and their mothers were systematically less likely to receive the other PHC interventions. These associations were particularly marked for 4+ ANC visits and institutional delivery and modest for careseeking behaviour. Our stratified analyses confirm a systematic disadvantage of unvaccinated children and their families with respect to obtaining other health services in all levels of household wealth and country income.

INTERPRETATION

We suggested that lack of vaccination goes hand in hand with missing out on other health interventions. This represents an opportunity for integrated delivery strategies that may more efficiently reduce inequalities in health service coverage.

FUNDING

Bill & Melinda Gates Foundation, Gavi, the Vaccine Alliance, The Wellcome Trust, Associação Brasileira de Saúde Coletiva and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior.

Zero-dose children and the immunisation cascade: Understanding immunisation pathways in low and middle-income countries

INTRODUCTION

Zero-dose prevalence refers to children who failed to receive any routine vaccination. Little is known about the "immunisation cascade" in low- and middle-income countries (LMICs), defined as how children move from zero dose to full immunisation.

METHODS

Using data from national surveys carried out in 92 LMICs since 2010 and focusing on the four basic vaccines delivered in infancy (BCG, polio, DPT and MCV), we describe zero-dose prevalence and the immunisation cascade in children aged 12 to 23 months. We also describe the most frequent combinations of vaccines (or co-coverage) among children who are partially immunized. Analyses are stratified by country income groups, household wealth quintiles derived from asset indices, sex of the child and area of residence. Results were pooled across countries using child populations as weights.

RESULTS

In the 92 countries, 7.7% were in the zero-dose group, and 3.3%, 3.4% and 14.6% received one, two or three vaccines, respectively; 70.9% received the four types and 59.9% of the total were fully immunised with all doses of the four vaccines. Three quarters (76.8%) of children who received the first vaccine received all four types. Among children with a single vaccine, polio was the most common in low- and lower-middle income countries, and BCG in upper-middle income countries. There were sharp inequalities according to household wealth, with zero-dose prevalence ranging from 12.5% in the poorest to 3.4% in the wealthiest quintile across all countries. The cascades were similar for boys and girls. In terms of dropout, 4% of children receiving BCG did not receive DPT1, 14% receiving DPT1 did not receive DPT3, and 9% receiving DPT3 did not progress to receive MCV.

INTERPRETATION

Focusing on zero-dose children is particularly important because those who are reached with the first vaccine are highly likely to also receive remaining vaccines.

[Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER Statement]

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 (http://gather-statement.org).

Monitoring universal health coverage within the Sustainable Development Goals: development and baseline data for an index of essential health services

BACKGROUND

Achieving universal health coverage, including quality essential service coverage and financial protection for all, is target 3.8 of the Sustainable Development Goals (SDG). As a result, an index of essential health service coverage indicators was selected by the UN as SDG indicator 3.8.1. We have developed an index for measuring SDG 3.8.1, describe methods for compiling the index, and report baseline results for 2015.

METHODS

16 tracer indicators were selected for the index, which included four from within each of the categories of reproductive, maternal, newborn, and child health; infectious disease; non-communicable diseases; and service capacity and access. Indicator data for 183 countries were taken from UN agency estimates or databases, supplemented with submissions from national focal points during a WHO country consultation. The index was computed using geometric means, and a subset of tracer indicators were used to summarise inequalities.

FINDINGS

On average, countries had primary data since 2010 for 72% of the final set of indicators. The median national value for the service coverage index was 65 out of 100 (range 22-86). The index was highly correlated with other summary measures of health, and after controlling for gross national income and mean years of adult education, was associated with 21 additional years of life expectancy over the observed range of country values. Across 52 countries with sufficient data, coverage was 1% to 66% lower among the poorest quintile as compared with the national population. Sensitivity analyses suggested ranks implied by the index are fairly stable across alternative calculation methods.

INTERPRETATION

Service coverage within universal health coverage can be measured with an index of tracer indicators. Our universal health coverage service coverage index is simple to compute by use of available country data and can be refined to incorporate relevant indicators as they become available through SDG monitoring.

FUNDING

Ministry of Health, Japan, and the Rockefeller Foundation.

Estimating The Potential Impact Of Insurance Expansion On Undiagnosed And Uncontrolled Chronic Conditions

Policy makers have paid considerable attention to the financial implications of insurance expansion under the Affordable Care Act (ACA), but there is little evidence of the law's potential health effects. To gain insight into these effects, we analyzed data for 1999-2012 from the National Health and Nutrition Examination Survey to evaluate relationships between health insurance and the diagnosis and management of diabetes, hypercholesterolemia, and hypertension. People with insurance had significantly higher probabilities of diagnosis than matched uninsured people, by 14 percentage points for diabetes and hypercholesterolemia and 9 percentage points for hypertension. Among those with existing diagnoses, insurance was associated with significantly lower hemoglobin A1c (-0.58 percent), total cholesterol (-8.0 mg/dL), and systolic blood pressure (-2.9 mmHg). If the number of nonelderly Americans without health insurance were reduced by half, we estimate that there would be 1.5 million more people with a diagnosis of one or more of these chronic conditions and 659,000 fewer people with uncontrolled cases. Our findings suggest that the ACA could have significant effects on chronic disease identification and management, but policy makers need to consider the possible implications of those effects for the demand for health care services and spending for chronic disease.

Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement

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.

Correction: Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement

[This corrects the article DOI: 10.1371/journal.pmed.1002056.].

Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement

Gretchen Stevens and colleagues present the GATHER statement, which seeks to promote good practice in the reporting of global health estimates.

Neonatal cause-of-death estimates for the early and late neonatal periods for 194 countries: 2000-2013

Objective

To estimate cause-of-death distributions in the early (0–6 days of age) and late (7–27 days of age) neonatal periods, for 194 countries between 2000 and 2013.

Methods

For 65 countries with high-quality vital registration, we used each country’s observed early and late neonatal proportional cause distributions. For the remaining 129 countries, we used multinomial logistic models to estimate these distributions. For countries with low child mortality we used vital registration data as inputs and for countries with high child mortality we used neonatal cause-of-death distribution data from studies in similar settings. We applied cause-specific proportions to neonatal death estimates from the United Nations Inter-agency Group for Child Mortality Estimation, by country and year, to estimate cause-specific risks and numbers of deaths.

Findings

Over time, neonatal deaths decreased for most causes. Of the 2.8 million neonatal deaths in 2013, 0.99 million deaths (uncertainty range: 0.70–1.31) were estimated to be caused by preterm birth complications, 0.64 million (uncertainty range: 0.46–0.84) by intrapartum complications and 0.43 million (uncertainty range: 0.22–0.66) by sepsis and other severe infections. Preterm birth (40.8%) and intrapartum complications (27.0%) accounted for most early neonatal deaths while infections caused nearly half of late neonatal deaths. Preterm birth complications were the leading cause of death in all regions of the world.

Conclusion

The neonatal cause-of-death distribution differs between the early and late periods and varies with neonatal mortality rate level. To reduce neonatal deaths, effective interventions to address these causes must be incorporated into policy decisions.

Spline-based modelling of trends in the force of HIV infection, with application to the UNAIDS Estimation and Projection Package

Objective

We previously developed a flexible specification of the UNAIDS Estimation and Projection Package (EPP) that relied on splines to generate time-varying values for the force of infection parameter. Here, we test the feasibility of this approach for concentrated HIV/AIDS epidemics with very sparse data and compare two methods for making short-term future projections with the spline-based model.

Methods

Penalised B-splines are used to model the average infection risk over time within the EPP 2011 modelling framework, which includes antiretroviral treatment effects and CD4 cell count progression, and is fit to sentinel surveillance prevalence data with a Bayesian algorithm. We compare two approaches for future projections: (1) an informative prior related to equilibrium prevalence and (2) a random walk formulation.

Results

The spline-based model produced plausible fits across a range of epidemics, which included 87 subpopulations from 14 countries with concentrated epidemics and 75 subpopulations from 33 countries with generalised epidemics. The equilibrium prior and random walk approaches to future projections yielded similar prevalence estimates, and both performed well in tests of out-of-sample predictive validity for prevalence. In contrast, in some cases the two approaches varied substantially in estimates of incidence, with the random walk formulation avoiding extreme changes in incidence.

Conclusions

A spline-based approach to allowing the force of infection parameter to vary over time within EPP 2011 is robust across a diverse array of epidemics, including concentrated ones with limited surveillance data. Future work on the EPP model should consider the impact that different modelling approaches have on estimates of HIV incidence.

National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

Objectives

Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors.

Methods

For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals.

Results

Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5.

Conclusions

Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence.

Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010

BACKGROUND

Measurement of the global burden of disease with disability-adjusted life-years (DALYs) requires disability weights that quantify health losses for all non-fatal consequences of disease and injury. There has been extensive debate about a range of conceptual and methodological issues concerning the definition and measurement of these weights. Our primary objective was a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach.

METHODS

We surveyed respondents in two ways: household surveys of adults aged 18 years or older (face-to-face interviews in Bangladesh, Indonesia, Peru, and Tanzania; telephone interviews in the USA) between Oct 28, 2009, and June 23, 2010; and an open-access web-based survey between July 26, 2010, and May 16, 2011. The surveys used paired comparison questions, in which respondents considered two hypothetical individuals with different, randomly selected health states and indicated which person they regarded as healthier. The web survey added questions about population health equivalence, which compared the overall health benefits of different life-saving or disease-prevention programmes. We analysed paired comparison responses with probit regression analysis on all 220 unique states in the study. We used results from the population health equivalence responses to anchor the results from the paired comparisons on the disability weight scale from 0 (implying no loss of health) to 1 (implying a health loss equivalent to death). Additionally, we compared new disability weights with those used in WHO's most recent update of the Global Burden of Disease Study for 2004.

FINDINGS

13,902 individuals participated in household surveys and 16,328 in the web survey. Analysis of paired comparison responses indicated a high degree of consistency across surveys: correlations between individual survey results and results from analysis of the pooled dataset were 0·9 or higher in all surveys except in Bangladesh (r=0·75). Most of the 220 disability weights were located on the mild end of the severity scale, with 58 (26%) having weights below 0·05. Five (11%) states had weights below 0·01, such as mild anaemia, mild hearing or vision loss, and secondary infertility. The health states with the highest disability weights were acute schizophrenia (0·76) and severe multiple sclerosis (0·71). We identified a broad pattern of agreement between the old and new weights (r=0·70), particularly in the moderate-to-severe range. However, in the mild range below 0·2, many states had significantly lower weights in our study than previously.

INTERPRETATION

This study represents the most extensive empirical effort as yet to measure disability weights. By contrast with the popular hypothesis that disability assessments vary widely across samples with different cultural environments, we have reported strong evidence of highly consistent results.

FUNDING

Bill & Melinda Gates Foundation.

Modelling national HIV/AIDS epidemics: revised approach in the UNAIDS Estimation and Projection Package 2011

Objective

United Nations Programme on HIV/AIDS reports regularly on estimated levels and trends in HIV/AIDS epidemics, which are evaluated using an epidemiological model within the Estimation and Projection Package (EPP). The relatively simple four-parameter model of HIV incidence used in EPP through the previous round of estimates has encountered challenges when attempting to fit certain data series on prevalence over time, particularly in settings with long running epidemics where prevalence has increased recently. To address this, the most recent version of the modelling package (EPP 2011) includes a more flexible epidemiological model that allows HIV infection risk to vary over time. This paper describes the technical details of this flexible approach to modelling HIV transmission dynamics within EPP 2011.

Methodology

For the flexible modelling approach, the force of infection parameter, r, is allowed to vary over time through a random walk formulation, and an informative prior distribution is used to improve short-term projections beyond the last year of data. Model parameters are estimated using a Bayesian estimation approach in which models are fit to HIV seroprevalence data from surveillance sites.

Results

This flexible model can yield better estimates of HIV prevalence over time in situations where the classic EPP model has difficulties, such as in Uganda, where prevalence is no longer falling. Based on formal out-of-sample projection tests, the flexible modelling approach also improves predictions and CIs for extrapolations beyond the last observed data point.

Conclusions

We recommend use of a flexible modelling approach where data are sufficient (eg, where at least 5 years of observations are available), and particularly where an epidemic is beyond its peak.

Intervention strategies to reduce the burden of non-communicable diseases in Mexico: cost effectiveness analysis

OBJECTIVE

To inform decision making regarding intervention strategies against non-communicable diseases in Mexico, in the context of health reform.

DESIGN

Cost effectiveness analysis based on epidemiological modelling.

INTERVENTIONS

101 intervention strategies relating to nine major clusters of non-communicable disease: depression, heavy alcohol use, tobacco use, cataracts, breast cancer, cervical cancer, chronic obstructive pulmonary disease, cardiovascular disease, and diabetes.

DATA SOURCES

Mexican data sources were used for most key input parameters, including administrative registries; disease burden and population estimates; household surveys; and drug price databases. These sources were supplemented as needed with estimates for Mexico from the WHO-CHOICE unit cost database or with estimates extrapolated from the published literature.

MAIN OUTCOME MEASURES

Population health outcomes, measured in disability adjusted life years (DALYs); costs in 2005 international dollars ($Int); and costs per DALY.

RESULTS

Across 101 intervention strategies examined in this study, average yearly costs at the population level would range from around ≤$Int1m (such as for cataract surgeries) to >$Int1bn for certain strategies for primary prevention in cardiovascular disease. Wide variation also appeared in total population health benefits, from <1000 DALYs averted a year (for some components of cancer treatments or aspirin for acute ischaemic stroke) to >300,000 averted DALYs (for aggressive combinations of interventions to deal with alcohol use or cardiovascular risks). Interventions in this study spanned a wide range of average cost effectiveness ratios, differing by more than three orders of magnitude between the lowest and highest ratios. Overall, community and public health interventions such as non-personal interventions for alcohol use, tobacco use, and cardiovascular risks tended to have lower cost effectiveness ratios than many clinical interventions (of varying complexity). Even within the community and public health interventions, however, there was a 200-fold difference between the most and least cost effective strategies examined. Likewise, several clinical interventions appeared among the strategies with the lowest average cost effectiveness ratios-for example, cataract surgeries.

CONCLUSIONS

Wide variations in costs and effects exist within and across intervention categories. For every major disease area examined, at least some strategies provided excellent value for money, including both population based and personal interventions.

Simulation methods to estimate design power: an overview for applied research

BACKGROUND

Estimating the required sample size and statistical power for a study is an integral part of study design. For standard designs, power equations provide an efficient solution to the problem, but they are unavailable for many complex study designs that arise in practice. For such complex study designs, computer simulation is a useful alternative for estimating study power. Although this approach is well known among statisticians, in our experience many epidemiologists and social scientists are unfamiliar with the technique. This article aims to address this knowledge gap.

METHODS

We review an approach to estimate study power for individual- or cluster-randomized designs using computer simulation. This flexible approach arises naturally from the model used to derive conventional power equations, but extends those methods to accommodate arbitrarily complex designs. The method is universally applicable to a broad range of designs and outcomes, and we present the material in a way that is approachable for quantitative, applied researchers. We illustrate the method using two examples (one simple, one complex) based on sanitation and nutritional interventions to improve child growth.

RESULTS

We first show how simulation reproduces conventional power estimates for simple randomized designs over a broad range of sample scenarios to familiarize the reader with the approach. We then demonstrate how to extend the simulation approach to more complex designs. Finally, we discuss extensions to the examples in the article, and provide computer code to efficiently run the example simulations in both R and Stata.

CONCLUSIONS

Simulation methods offer a flexible option to estimate statistical power for standard and non-traditional study designs and parameters of interest. The approach we have described is universally applicable for evaluating study designs used in epidemiologic and social science research.

Flexible epidemiological model for estimates and short-term projections in generalised HIV/AIDS epidemics

Objective

UNAIDS and country analysts use a simple infectious disease model, embedded in the Estimation and Projection Package (EPP), to generate annual updates on the global HIV/AIDS epidemic. Our objective was to develop modifications to the current model that improve fit to recently observed prevalence trends across countries.

Methods

Our proposed alternative to the current EPP approach simplifies the model structure and explicitly models changes in average infection risk over time, operationalised using penalised B-splines in a Bayesian framework. We also present an alternative approach to initiating the epidemic that improves standardisation and efficiency, and add an informative prior distribution for changes in infection risk beyond the last data point that enhances the plausibility of short-term extrapolations.

Results

The spline-based model produces better fits than the current model to observed prevalence trends in settings that have recently experienced levelling or rising prevalence following a steep decline, such as Uganda and urban Rwanda. The model also predicts a deceleration of the decline in prevalence for countries with recent experience of steady declines, such as Kenya and Zimbabwe. Estimates and projections from our alternative model are comparable to those from the current model where the latter performs well.

Conclusions

A more flexible epidemiological model that accommodates changing infection risk over time can provide better estimates and short-term projections of HIV/AIDS incidence, prevalence and mortality than the current EPP model. The alternative model specification can be incorporated easily into existing analytical tools that are used to produce updates on the global HIV/AIDS epidemic.

Cost effectiveness analysis of strategies to combat HIV/AIDS in developing countries

OBJECTIVE

To assess the costs and health effects of a range of interventions for preventing the spread of HIV and for treating people with HIV/AIDS in the context of the millennium development goal for combating HIV/AIDS.

DESIGN

Cost effectiveness analysis based on an epidemiological model.

SETTING

Analyses undertaken for two regions classified using the WHO epidemiological grouping-Afr-E, countries in sub-Saharan Africa with very high adult and high child mortality, and Sear-D, countries in South East Asia with high adult and high child mortality.

DATA SOURCES

Biological and behavioural parameters from clinical and observational studies and population based surveys. Intervention effects and resource inputs based on published reports, expert opinion, and the WHO-CHOICE database.

MAIN OUTCOME MEASURES

Costs per disability adjusted life year (DALY) averted in 2000 international dollars (Int dollars).

RESULTS

In both regions interventions focused on mass media, education and treatment of sexually transmitted infections for female sex workers, and treatment of sexually transmitted infections in the general population cost < Int150 dollars per DALY averted. Voluntary counselling and testing costs < Int350 dollars per DALY averted in both regions, while prevention of mother to child transmission costs < Int50 dollars per DALY averted in Afr-E but around Int850 dollars per DALY in Sear-D. School based education strategies and various antiretroviral treatment strategies cost between Int500 dollars and Int5000 dollars per DALY averted.

CONCLUSIONS

Reducing HIV transmission could be done most efficiently through mass media campaigns, interventions for sex workers and treatment of sexually transmitted infections where resources are most scarce. However, prevention of mother to child transmission, voluntary counselling and testing, and school based education would yield further health gains at higher budget levels and would be regarded as cost effective or highly cost effective based on standard international benchmarks. Antiretroviral therapy is at least as cost effective in improving population health as some of these interventions.

Prevention and treatment of human immunodeficiency virus/acquired immunodeficiency syndrome in resource-limited settings

Strategies for confronting the epidemic of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) have included a range of different approaches that focus on prevention and treatment. However, debate persists over what levels of emphasis are appropriate for the different components of the global response. This paper presents an overview of this debate and briefly summarizes the evidence on a range of interventions designed to prevent the spread of HIV infection, paying particular attention to voluntary counselling and testing, treatment for sexually transmitted infections and prevention of mother-to-child transmission. We also review the experience with antiretroviral therapy to date in terms of response rates and survival rates, adherence, drug resistance, behavioural change and epidemiological impact. Although various studies have identified strategies with proven effectiveness in reducing the risks of HIV infection and AIDS mortality, considerable uncertainties remain. Successful integration of treatment and prevention of HIV/AIDS will require a balanced approach and rigorous monitoring of the impact of programmes in terms of both individual and population outcomes.