Can Disease-Specific Funding Harm Health? in the Shadow of HIV/AIDS Service Expansion

Using machine learning to estimate health spillover effects

We develop a nonparametric model to study health spillover effects of policy interventions. We use double/debiased machine learning to estimate the model using data from 74 hospitals in Rio de Janeiro, Brazil, and examine cross-patient spillover effects during the COVID-19 pandemic. The pandemic forced hospitals to develop new protocols to offer intensive care to both COVID and non-COVID patients. Our results show that the need to care for COVID patients affects health outcomes of non-COVID patients. Controlling for a number of confounders, we find that mortality rates and length of stay of non-COVID ICU patients increase when hospitals simultaneously offer intensive care to both types of patients. Policy simulations suggest that an increase in the number of ICU beds can counter morbidity spillover, but it is unlikely to be a feasible approach to counter mortality spillover.

Early life adversity, biological adaptation, and human capital: evidence from an interrupted malaria control program in Zambia

Growing evidence from evolutionary biology demonstrates how early life shocks trigger physiological changes designed to be adaptive in challenging environments. We examine the implications of one type of physiological adaptation - immunity formation - for human capital accumulation. Using variation in early life malaria risk generated by an interrupted disease control program in Zambia, we show that exposure to infectious diseases during the first two years of life can reduce the harmful effects of malaria exposure on cognitive development during the preschool years. These findings suggest a non-linear and trajectory-dependent relationship between early life adversity and human capital formation.

How can we evaluate the cost-effectiveness of health system strengthening? A typology and illustrations

Health interventions often depend on a complex system of human and capital infrastructure that is shared with other interventions, in the form of service delivery platforms, such as healthcare facilities, hospitals, or community services. Most forms of health system strengthening seek to improve the efficiency or effectiveness of such delivery platforms. This paper presents a typology of ways in which health system strengthening can improve the economic efficiency of health services. Three types of health system strengthening are identified and modelled: (1) investment in the efficiency of an existing shared platform that generates positive benefits across a range of existing interventions; (2) relaxing a capacity constraint of an existing shared platform that inhibits the optimization of existing interventions; (3) providing an entirely new shared platform that supports a number of existing or new interventions. Theoretical models are illustrated with examples, and illustrate the importance of considering the portfolio of interventions using a platform, and not just piecemeal individual analysis of those interventions. They show how it is possible to extend principles of conventional cost-effectiveness analysis to identify an optimal balance between investing in health system strengthening and expenditure on specific interventions. The models developed in this paper provide a conceptual framework for evaluating the cost-effectiveness of investments in strengthening healthcare systems and, more broadly, shed light on the role that platforms play in promoting the cost-effectiveness of different interventions.

The effect of facility-based antiretroviral therapy programs on outpatient services in Kenya and Uganda

Background

Considerable debate exists concerning the effects of antiretroviral therapy (ART) service scale-up on non-HIV services and overall health system performance in sub-Saharan Africa. In this study, we examined whether ART services affected trends in non-ART outpatient department (OPD) visits in Kenya and Uganda.

Methods

Using a nationally representative sample of health facilities in Kenya and Uganda, we estimated the effect of ART programs on OPD visits from 2007 to 2012. We modeled the annual percent change in non-ART OPD visits using hierarchical mixed-effects linear regressions, controlling for a range of facility characteristics. We used four different constructs of ART services to capture the different ways in which the presence, growth, overall, and relative size of ART programs may affect non-ART OPD services.

Results

Our final sample included 321 health facilities (140 in Kenya and 181 in Uganda). On average, OPD and ART visits increased steadily in Kenya and Uganda between 2007 and 2012. For facilities where ART services were not offered, the average annual increase in OPD visits was 4·2% in Kenya and 13·5% in Uganda. Among facilities that provided ART services, we found average annual OPD volume increases of 7·2% in Kenya and 5·6% in Uganda, with simultaneous annual increases of 13·7% and 12·5% in ART volumes. We did not find a statistically significant relationship between annual changes in OPD services and the presence, growth, overall, or relative size of ART services. However, in a subgroup analysis, we found that Ugandan hospitals that offered ART services had statistically significantly less growth in OPD visits than Ugandan hospitals that did not provide ART services.

Conclusions

Our findings suggest that ART services in Kenya and Uganda did not have a statistically significant deleterious effects on OPD services between 2007 and 2012, although subgroup analyses indicate variation by facility type. Our findings are encouraging, particularly given recent recommendations for universal access to ART, demonstrating that expanding ART services is not inherently linked to declines in other health services in sub-Saharan Africa.

Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals

BACKGROUND

Despite remarkable progress in the improvement of child survival between 1990 and 2015, the Millennium Development Goal (MDG) 4 target of a two-thirds reduction of under-5 mortality rate (U5MR) was not achieved globally. In this paper, we updated our annual estimates of child mortality by cause to 2000-15 to reflect on progress toward the MDG 4 and consider implications for the Sustainable Development Goals (SDG) target for child survival.

METHODS

We increased the estimation input data for causes of deaths by 43% among neonates and 23% among 1-59-month-olds, respectively. We used adequate vital registration (VR) data where available, and modelled cause-specific mortality fractions applying multinomial logistic regressions using adequate VR for low U5MR countries and verbal autopsy data for high U5MR countries. We updated the estimation to use Plasmodium falciparum parasite rate in place of malaria index in the modelling of malaria deaths; to use adjusted empirical estimates instead of modelled estimates for China; and to consider the effects of pneumococcal conjugate vaccine and rotavirus vaccine in the estimation.

FINDINGS

In 2015, among the 5·9 million under-5 deaths, 2·7 million occurred in the neonatal period. The leading under-5 causes were preterm birth complications (1·055 million [95% uncertainty range (UR) 0·935-1·179]), pneumonia (0·921 million [0·812 -1·117]), and intrapartum-related events (0·691 million [0·598 -0·778]). In the two MDG regions with the most under-5 deaths, the leading cause was pneumonia in sub-Saharan Africa and preterm birth complications in southern Asia. Reductions in mortality rates for pneumonia, diarrhoea, neonatal intrapartum-related events, malaria, and measles were responsible for 61% of the total reduction of 35 per 1000 livebirths in U5MR in 2000-15. Stratified by U5MR, pneumonia was the leading cause in countries with very high U5MR. Preterm birth complications and pneumonia were both important in high, medium high, and medium child mortality countries; whereas congenital abnormalities was the most important cause in countries with low and very low U5MR.

INTERPRETATION

In the SDG era, countries are advised to prioritise child survival policy and programmes based on their child cause-of-death composition. Continued and enhanced efforts to scale up proven life-saving interventions are needed to achieve the SDG child survival target.

FUNDING

Bill & Melinda Gates Foundation, WHO.