I have read the journal's policy and the authors of this manuscript have the following competing interests: SB receives a stipend as a specialty consulting editor for PLOS Medicine and serves on the journal's editorial board. The authors have declared that no other competing interests exist.
Since 2015, a major economic crisis in Brazil has led to increasing poverty and the implementation of long-term fiscal austerity measures that will substantially reduce expenditure on social welfare programmes as a percentage of the country’s GDP over the next 20 years. The Bolsa Família Programme (BFP)—one of the largest conditional cash transfer programmes in the world—and the nationwide primary healthcare strategy (Estratégia Saúde da Família [ESF]) are affected by fiscal austerity, despite being among the policy interventions with the strongest estimated impact on child mortality in the country. We investigated how reduced coverage of the BFP and ESF—compared to an alternative scenario where the level of social protection under these programmes is maintained—may affect the under-five mortality rate (U5MR) and socioeconomic inequalities in child health in the country until 2030, the end date of the Sustainable Development Goals.
We developed and validated a microsimulation model, creating a synthetic cohort of all 5,507 Brazilian municipalities for the period 2017–2030. This model was based on the longitudinal dataset and effect estimates from a previously published study that evaluated the effects of poverty, the BFP, and the ESF on child health. We forecast the economic crisis and the effect of reductions in BFP and ESF coverage due to current fiscal austerity on the U5MR, and compared this scenario with a scenario where these programmes maintain the levels of social protection by increasing or decreasing with the size of Brazil’s vulnerable populations (policy response scenarios). We used fixed effects multivariate regression models including BFP and ESF coverage and accounting for secular trends, demographic and socioeconomic changes, and programme duration effects. With the maintenance of the levels of social protection provided by the BFP and ESF, in the most likely economic crisis scenario the U5MR is expected to be 8.57% (95% CI: 6.88%–10.24%) lower in 2030 than under fiscal austerity—a cumulative 19,732 (95% CI: 10,207–29,285) averted under-five deaths between 2017 and 2030. U5MRs from diarrhoea, malnutrition, and lower respiratory tract infections are projected to be 39.3% (95% CI: 36.9%–41.8%), 35.8% (95% CI: 31.5%–39.9%), and 8.5% (95% CI: 4.1%–12.0%) lower, respectively, in 2030 under the maintenance of BFP and ESF coverage, with 123,549 fewer under-five hospitalisations from all causes over the study period. Reduced coverage of the BFP and ESF will also disproportionately affect U5MR in the most vulnerable areas, with the U5MR in the poorest quintile of municipalities expected to be 11.0% (95% CI: 8.0%–13.8%) lower in 2030 under the maintenance of BFP and ESF levels of social protection than under fiscal austerity, compared to no difference in the richest quintile. Declines in health inequalities over the last decade will also stop under a fiscal austerity scenario: the U5MR concentration index is expected to remain stable over the period 2017–2030, compared to a 13.3% (95% CI: 5.6%–21.8%) reduction under the maintenance of BFP and ESF levels of protection. Limitations of our analysis are the ecological nature of the study, uncertainty around future macroeconomic scenarios, and potential changes in other factors affecting child health. A wide range of sensitivity analyses were conducted to minimise these limitations.
The implementation of fiscal austerity measures in Brazil can be responsible for substantively higher childhood morbidity and mortality than expected under maintenance of social protection—threatening attainment of Sustainable Development Goals for child health and reducing inequality.
In a modeling study, Davide Rasella and colleagues investigate the possible consequences for child illness and mortality of different levels of coverage by social protection programs in Brazil.
There is little evidence on the health impacts of economic crisis and fiscal austerity measures in low- and middle-income countries with fragile social protection systems and high poverty rates. Furthermore, there is poor understanding of how austerity measures could threaten attainment of the Sustainable Development Goals (SDGs) in these countries.
A platform of long-term fiscal austerity measures is underway in Brazil in response to acute economic and political crises. Little is known about the possible impact of the planned reductions (as percentage of country GDP) in expenditure on social welfare programmes over the next two decades on health outcomes.
We forecast the effects of the economic crisis and austerity measures on two key social welfare programmes (the Bolsa Família Programme [BFP] and Estratégia Saúde da Família [ESF]) and on child morbidity and mortality in Brazil using a synthetic cohort of 5,507 municipalities using a robust modelling technique—discrete-time microsimulation—with municipality-specific time trends and parameters.
Our forecasts indicate that over the period 2017–2030, reducing coverage of the BFP and ESF, compared with maintaining their coverage, could result in a higher child mortality rate—up to 8.6% higher in 2030. These austerity measures would then be responsible for almost 20,000 avoidable childhood deaths and 124,000 avoidable childhood hospitalisations between 2017 and 2030.
According to our estimates, poorer municipalities would be disproportionately affected, ensuring that Brazil’s already high inequalities would persist until at least 2030. In contrast, maintaining BFP and ESF coverage would contribute to reducing these high inequalities, in line with the SDGs.
A range of sensitivity analyses show that, even under different simulated intensities and durations of economic crisis and reductions in BFP and ESF coverage, the numbers of avoidable childhood deaths and hospitalisations under austerity measures are expected to be high.
Our study suggests that reduced coverage of poverty-alleviation and primary care programmes may result in a substantial number of preventable child deaths and hospitalisations in Brazil.
These austerity measures will disproportionately impact child mortality in the poorest municipalities, disrupting previous declines in inequality in child health outcomes.
The implementation of austerity measures in LMICs during economic crises is likely to threaten achievement of the SDGs related to poverty reduction, improving health, and reducing health inequality.
Several studies have examined the effects of economic crises on health outcomes in high-income countries [
The Brazilian economy experienced one of its strongest economic crises in recent years, with GDP falling by more than 8% since mid-2014 [
Since 2014, a sharp and deep recession in Brazil has unfolded, with annual GDP contractions of 3.8% and 3.6% in 2015 and 2016, respectively [
Since 2016, in the depths of the economic crisis, a newly installed government has initiated a range of fiscal austerity measures [
For healthcare spending, the comparison is between the real spending in the period 2004–2015 and the simulated spending if the Constitutional Amendment 95 (EC95) were applied during the same period; for social assistance, the comparison is between the simulated spending necessary to maintain the existing levels of protection for the years 2017–2028 and the simulated spending according to the currently implemented EC95.
Effectively, there is no possibility of real growth in healthcare and social protection expenditures from the federal government, which is important given the current low expenditure on health from public sources (relative to other middle-income countries and countries in Latin America), sizeable predicted population growth in Brazil, and near certain growth in costly health burdens. It is highly likely that the Bolsa Família Programme (BFP) and Estratégia Saúde da Família (ESF) budgets, as major components of the federal health and social protection budget, will be directly affected and their coverage reduced proportionally to EC95 budget reductions (see
We envision two policy response scenarios: one that follows EC95, with reductions in BFP and ESF coverage (the austerity scenario), and a second hypothetical situation, where funds for the BFP and ESF are increased in line with increases in poverty (a maintenance of social protection scenario).
While economic recession in Brazil technically ended in late 2017, recovery is likely to be fragile given the depth of the economic contraction since 2014 and the ongoing political crisis in the country; continued increases in unemployment, income inequality, and poverty are indicative of a persistent economic crisis [
The programmes most likely to be affected by austerity measures include the BFP—one of the largest conditional cash transfer programmes of the world—and the ESF—Brazil’s national primary healthcare strategy and principal vehicle for achieving universal health coverage. Available evidence indicates that these programmes have reduced child mortality and health inequalities [
The BFP was launched in 2003 and expanded quickly. In 2016, it covered 13.6 million families (approximately 25% of the Brazilian population) with a budget of US$8.8 billion—one of the largest conditional cash transfer programmes in the world. Conditional cash transfer programmes are social security systems that provide funds for eligible low-income families, but only if conditions (or conditionalities), usually related to the health and education of their children, are met [
The ESF is a community-based model of primary healthcare, centred on family health teams staffed by a doctor, nurse, nurse assistant, and community health workers providing healthcare to locally defined populations. Approximately 3,500 individuals are registered per team and receive a broad package of primary care services including basic curative care, health promotion, health education, and specific targeted programmes addressing women and children’s health, HIV/AIDS, infectious diseases, and cardiovascular health. A sizeable evidence base has grown demonstrating the impact of the ESF, including on child health. High municipal ESF coverage was associated with a 12% reduction in U5MR over the period 2004–2009 [
Despite an increasing number of retrospective studies on the effects of economic crisis on health outcomes, systematic literature searches yielded no studies forecasting health impacts of economic crisis or austerity measures in LMICs (
This study uses discrete-time microsimulation to forecast the impact of the economic crisis and policy response scenarios in Brazil on overall and cause-specific U5MRs and the under-five hospitalisation rate (U5HR) from 2017 to 2030.
Microsimulation is increasingly used in epidemiology and is particularly useful to evaluate both overall and subgroup impacts of public policies [
The modelling approach adopted for this study was developed in two stages. First, we created a synthetic cohort of all Brazilian municipalities for the period 2010–2030 as an extension, or post-sample forecasting, of a longitudinal dataset for the period 2000–2010 used previously in retrospective impact evaluations [
We simulated municipality-specific changes in poverty rates and the other socioeconomic variables over time according to economic crisis scenarios for the years 2010–2030, and BFP and ESF coverage according to policy response scenarios. Changes in relevant demographic variables over time, such as fertility rate and number of live births per municipality, were also modelled.
Second, for each year and each municipality, U5MR and U5HR were estimated as outcomes of the same longitudinal fixed effects regressions using the forecast demographic, socioeconomic, and exposure variables (BFP and ESF coverage) as input values. Fixed effects are used in impact evaluations, both retrospective and forecast, because they include a term to control for unobserved characteristics of the unit of analysis that are constant during the study period, such as some geographical, historical, or sociocultural aspects of each municipality [
Two types of input data were introduced as parameters in the models (
Variable | Mean values | Effect sizes (rate ratios) | Data sources of municipal values |
---|---|---|---|
Municipal BFP coverage | See |
See |
Ministry of Social Development |
Municipal ESF coverage | See |
See |
Datasus, Ministry of Health |
Monthly income per capita | See |
See |
National census data, IBGE |
Poverty rate | See |
See |
National census data, IBGE |
Illiteracy rate | See |
See |
National census data, IBGE |
Fertility rate | See |
See |
National census data, IBGE |
Percentage of the population living in households with adequate sanitation | See |
See |
National census data, IBGE |
BFP, Bolsa Família Programme; ESF, Estratégia Saúde da Família; IBGE, Instituto Brasileiro de Geografia e Estatística.
We simulated three economic crisis scenarios using poverty rates and mean per capita income from National Household Surveys for the years 2011–2015 and microsimulation from the World Bank for the time periods indicated below [
Economic crisis scenario 1: A milder and shorter economic crisis with a smaller yearly increase (0.55%) in the poverty rate lasting 3 years (from 2015 to 2017)
Economic crisis scenario 2: A medium economic crisis with a larger yearly increase (0.80%) in the poverty rate sustained over 5 years (from 2015 to 2019), the most probable at the time of writing
Economic crisis scenario 3: A longer economic crisis with the same percent increase in the poverty rate as scenario 2, but sustained over 7 years (from 2015 to 2021)
In response to the economic crisis, two policy responses were considered in the main analysis, both starting from 2017 (the current year of the study):
Fiscal austerity: This started to be implemented at the beginning of 2017. Estimates were based on simulations of the impact of the already implemented austerity measures (mainly EC95) on the budget for social protection and healthcare until 2030 [
Social protection: Maintaining social assistance and healthcare coverage in response to the economic crisis in the period 2017–2030. This response was projected as increases in BFP and ESF coverage proportional to increases in the poverty rate and also, at the end of the economic crisis, decreases in the BFP proportional to poverty reductions and a return to pre-crisis coverage levels for the ESF.
Additionally, a broad range of economic crisis and policy response scenarios were modelled as sensitivity analyses (see
Using the 2010–2030 synthetic cohort of covariates and exposure variables (BFP and ESF coverage)—an extension of the retrospective cohort based, as explained above, on real data—for different scenarios, a post-sample forecasting of the U5MRs and U5HRs was performed. Fixed effects predictors were used based on the fixed effects negative binomial regression models in the previous retrospective impact evaluation [
U5MRs for specific causes was modelled based on estimates from the reference retrospective study, which showed a stronger effect of consolidated BFP and ESF coverage (high coverage for at least 4 years) on deaths from malnutrition, diarrhoeal diseases, and lower respiratory infections, than on deaths from other causes, with reductions in municipalities with consolidated coverage of 65%, 53%, and 20%, respectively [
For each outcome and each scenario, 10,000 simulations were performed using the Monte Carlo sampling method. This allows parameter values to vary in each simulation cycle according to their assumed underlying distribution. Mortality rates were modelled as negative binomial distributions, and other parameters as normal distributions. The effects of the independent variables—expressed as incidence rate ratios (IRRs)—were sampled from normal distributions calibrated with the mean and 95% confidence intervals of the IRR from the retrospective impact evaluation. For each year and each scenario, we obtained a distribution of 10,000 possible values of the outcome (U5MR or U5HR). We estimated the mean and the confidence interval using the 2.5% and 97.5% quantiles from this distribution. CIs are used in microsimulation to represent the uncertainty of the estimates [
To compare and quantify the expected differences in U5MR and U5HR for our policy response scenarios, we estimated the rate ratios between the two scenarios for each simulation, dividing the U5MR and U5HR in the social protection scenario by the U5MR and U5HR in the fiscal austerity scenario, and obtained the mean IRR with CI for all the simulations. These comparisons were also evaluated in terms of the differences in the total number of deaths and hospitalisations during the study period.
The models were coded and implemented in R version 3.4.0.
Municipalities were stratified based on quintiles of poverty rate in the baseline year of the simulation (2010), and comparisons between the scenarios described above were performed for each quintile. Changes in U5MR inequalities over time across municipalities were estimated using the U5MR concentration index by municipal poverty rate in the baseline year. Concentration indices are relative measures of inequality that, within health, quantify the gradient of a health outcome across the socioeconomic range. They are well-used measures of inequality as they indicate the extent to which health outcomes are concentrated among the disadvantaged (or the advantaged) [
All model parameters were derived from a retrospective impact evaluation [
External validation of the model was undertaken by comparing the overall national U5MR forecast by our microsimulation with the official Brazilian U5MR estimates during the years 2010–2013 [
The robustness of the results was verified through multiple sensitivity analyses. First, we tested the effect of different lengths and intensities of poverty rate increases during our simulated economic crisis scenarios. Differential poverty rate increases according to municipal characteristics at baseline (2010) were also tested, with larger increases in poverty in poorer municipalities and smaller increases in the wealthier municipalities. Second, a broad range of policy responses were tested, including slower reductions in BFP and ESF coverage (less than 4% yearly) under austerity scenarios and heterogeneous BFP and ESF reductions. Third, different values for the effect of the time variable representing secular changes over time were tested. We also evaluated the possibility that the fiscal austerity scenario would be able to reduce and shorten the economic crisis, while the maintenance of social protection would extend the period of economic crisis, comparing the two possible scenarios. All sensitivity analyses are detailed in
Under all economic crisis scenarios, poverty rates are forecast to increase, and income per capita to fall, in the coming years (
Economic crisis scenario | Variable | Year | |||||||
---|---|---|---|---|---|---|---|---|---|
2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2025 | 2030 | ||
Poverty | 13.6 | 15.4 | 16.8 | 15.9 | 15.1 | 14.4 | 11.4 | 9.2 | |
Income | 731.2 | 720.2 | 709.5 | 732.8 | 755.2 | 776.8 | 873.2 | 952.8 | |
Poverty | 13.9 | 15.9 | 17.4 | 18.5 | 19.4 | 18.4 | 14.4 | 11.5 | |
Income | 731.2 | 720.2 | 709.5 | 698.8 | 688.4 | 711.0 | 812.0 | 895.8 | |
Poverty | 13.9 | 15.9 | 17.4 | 18.5 | 19.4 | 20.2 | 15.7 | 12.5 | |
Income | 731.2 | 720.2 | 709.5 | 698.8 | 688.4 | 677.7 | 781.1 | 866.3 | |
Illiteracy | 12.3 | 11.6 | 11.1 | 10.5 | 10.0 | 9.5 | 7.6 | 6.2 | |
Fertility | 1.9 | 1.8 | 1.8 | 1.7 | 1.7 | 1.6 | 1.4 | 1.3 | |
Sanitation | 91.1 | 91.9 | 92.6 | 93.1 | 93.5 | 93.8 | 94.6 | 95.0 |
Income—mean monthly per capita income (Brazilian reais); poverty—percentage of population with an income of less than US$43 per month; illiteracy—percentage of those over 15 years of age who are illiterate; fertility rate—mean children per woman; sanitation—percentage of the population living in households with adequate sanitation.
Values of all variables in the study period are shown in
BFP, Bolsa Família Programme; ESF, Estratégia Saúde da Família.
From 2017 onwards, the two policy responses are associated with different U5MRs (
Economic crisis scenario | Rate ratio (confidence interval) by year | ||||||
---|---|---|---|---|---|---|---|
2015 | 2017 | 2018 | 2019 | 2020 | 2025 | 2030 | |
Economic crisis scenario 1 (shorter) | 1.000 |
0.987 |
0.982 |
0.976 |
0.970 |
0.946 |
0.930 |
Economic crisis scenario 2 (medium) | 1.000 |
0.987 |
0.975 |
0.964 |
0.956 |
0.930 |
0.914 |
Economic crisis scenario 3 (longer) | 1.000 |
0.987 |
0.975 |
0.964 |
0.950 |
0.921 |
0.905 |
BFP, Bolsa Família Programme; ESF, Estratégia Saúde da Família; Inf., infection; U5HR, under-five hospitalisation rate; U5MR, under-five mortality rate.
Attenuations in annual reductions in U5MR and U5HR are observed for both policy responses, but under the austerity scenario, increases in the U5MR are forecast for diarrhoeal diseases and malnutrition. Under the maintenance of social protection scenario, mortality from these causes would continue to decline, albeit at a slower rate, resulting in U5MRs in 2030 that are 39.3% (95% CI: 36.9%–41.8%) and 35.8% (95% CI: 31.5%–39.9%) lower for diarrhoeal diseases and malnutrition, respectively, than under austerity. For lower respiratory tract infections, by 2030 the U5MR would be 8.45% (95% CI: 4.16%–12.01%) lower with maintenance of social protection. The rate ratios for these causes of death are larger than for overall U5MR because the effects of the BFP and ESF were larger in the retrospective analysis (see
Stratification of changes in U5MR by quintiles of municipal-level poverty shows that the effects of the maintenance of social protection are greatest in the poorest municipalities (
BFP and ESF coverage given as percentage. Policy response—fiscal austerity: solid lines; policy response—social protection maintenance: dashed lines; black: first quintile (poorest); brown: second quintile; yellow: third quintile; orange: fourth quintile; red: fifth quintile (richest). BFP, Bolsa Família Programme; ESF, Estratégia Saúde da Família.
Under maintenance of social protection, the U5MR would be 11.01% (95% CI: 7.97%–13.83%) lower than under austerity in 2030 in the first (poorest) quintile (
Poverty quintile | Rate ratio (confidence interval) by year | |||
---|---|---|---|---|
2015 | 2020 | 2025 | 2030 | |
Poverty quintile 1 | 1.000 |
0.949 |
0.912 |
0.890 |
Poverty quintile 2 | 1.000 |
0.946 |
0.904 |
0.883 |
Poverty quintile 3 | 1.000 |
0.942 |
0.929 |
0.921 |
Poverty quintile 4 | 1.000 |
0.970 |
0.961 |
0.950 |
Poverty quintile 5 | 1.000 |
0.986 |
0.970 |
0.959 |
Results on the U5MRs from diarrhoea, malnutrition, and lower respiratory infections and hospitalisations are similar under the different economic crisis scenarios and have a similar dose–response relationship with the intensity of the crisis as for overall U5MR. Alternative inequality analyses under different economic scenarios also produce similar results. Even if different secular changes in U5MRs over time are introduced in the model, the comparison (in terms of either the IRR or avoided deaths) between scenarios remains unchanged. Sensitivity analyses show that varying the magnitude of BFP and ESF coverage reductions due to austerity measures do not affect our conclusions as all modelled reductions were associated with strong and statistically significant child mortality impacts. Our simulation where fiscal austerity shortened the economic crisis, while the maintenance of social protection extended it until 2030 shows that child mortality would still be 4.43% (95% CI: 2.79%–6.32%) lower in 2030 under the latter scenario.
Our findings show that levels of child mortality in Brazil are likely to be substantially different under a fiscal austerity scenario, modelled as a reduction in coverage of poverty-alleviation and primary care programmes, compared with a scenario where existing levels of social protection of these programmes are maintained and provide coverage of vulnerable populations. Our forecasts indicate that under a scenario that maintains social protection the U5MR would be 8.6% lower in 2030 than under an austerity scenario—with a cumulative impact of almost 20,000 averted under-five deaths over the period 2017–2030. U5MRs from diarrhoeal diseases and malnutrition would be 39.3% and 35.8% lower in 2030, respectively, and there would be 123,000 fewer under-five hospitalisations under the maintenance of social protection. According to our estimates, BFP and ESF coverage reductions would disproportionately impact child mortality in the poorest municipalities and contribute to the persistence of sizeable health inequalities, compromising efforts towards achieving both the third and tenth SDGs.
To our knowledge, this is the first study to evaluate the impact of fiscal austerity measures on health during an ongoing economic crisis in a middle-income country. Similar to Brazil, many other Latin American countries are experiencing economic crises that have stimulated policy-makers to consider fiscal austerity, potentially undermining the longstanding efforts to strengthen their welfare states [
Our prediction of higher mortality from diarrhoea and malnutrition under austerity is consistent with our retrospective evaluation, where the BFP and ESF had a considerably stronger effect on mortality from these causes than on overall U5MR [
The main strength of this study is the use of a synthetic cohort of 5,507 municipalities built as an extension of a pre-existing 10-year retrospective cohort used in previous impact evaluations [
There are pertinent limitations of the study, mainly stemming from uncertainty around the future macroeconomic scenarios in Brazil. This is due to the current unstable political and economic situation, creating uncertainty around the forecasting of poverty rates, income, and the other independent variables. Therefore, additional scenarios were forecast in sensitivity analyses, with all—even simulation of different intensities and lengths of the economic crisis—showing that the differences between the two policy scenarios (long-term austerity versus maintenance of social protection) remain large and of comparable magnitude (
Brazil has implemented bold policies to reduce poverty and achieve universal health coverage over the past 20 years [
In conclusion, the results of our study show that implementation of fiscal austerity measures could contribute to a large number of preventable child deaths and hospitalisations in Brazil, threatening attainment of the SDGs related to child health and inequalities.
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We thank Daniel Villela for his suggestions related to the implementation of the code for microsimulation.
Bolsa Família Programme
Constitutional Amendment 95
Estratégia Saúde da Família
incidence rate ratio
low- and middle-income countries
Sustainable Development Goals
under-five hospitalisation rate
under-five mortality rate