Impact of macro-fiscal determinants on health financing:empirical evidence from low-and middle-income countries

Background:Health financing is a major challenge in low-and middle-income counties(LMICs)for achieving Universal Health Coverage(UHC).Past studies have argued that the budgetary allocation on health financing depends on macrofiscal policies of an economy such as sustained economic growth and higher revenue mobilization.While the global financial crisis of late 2008 observed a shortage of financial resources in richer countries and adversely affected the health sector.Therefore,this study has examined the impact of macro-fiscal policies on health financing by adopting socioeconomic factors in 85 LMICs for the period 2000 to 2013.Methods:The study has employed the panel System Generalized Method of Moment model that captures the endogeneity problem in the regression estimation by adopting appropriate instrumental variables.Results:The elasticity of public health expenditure(PHE)with respect to macro-fiscal factors varies across LMICs.Tax revenue shows a positive and statistically significant relationship with PHE in full sample,pre-global financial crisis,middle-income,and coefficient value varies from 0.040 to 0.141%.Fiscal deficit and debt services payment shows a negative effect on PHE in full sample,as well as sub-samples and coefficient value,varies from 0.001 to 0.032%.Aging and per capita income show an expected positive relationship with PHE in LIMI countries.Conclusions:Favorable macro-fiscal policies would necessarily raise finance for the health sector development but the prioritization of health budget allocation during the crisis period depends on the nature of tax revenue mobilization and demand for health services.Therefore,the generation of health-specific revenues and effective usage of health budget would probably accelerate the progress towards the achievement of UHC.

Capacity-need gap in hospital resources for varying mitigation and containment strategies in India in the face of COVID-19 pandemic

Background:Due to uncertainties encompassing the transmission dynamics of COVID-19,mathematical models informing the trajectory of disease are being proposed throughout the world.Current pandemic is also characterized by surge in hospitalizations which has overwhelmed even the most resilient health systems.Therefore,it is imperative to assess health system preparedness in tandem with need projections for comprehensive outlook.Objective:We attempted this study to forecast the need for hospital resources for one year period and correspondingly assessed capacity and tipping points of Indian health system to absorb surges in need due to COVID-19.Methods:We employed age-structured deterministic SEIR model and modified it to allow for testing and isolation capacity to forecast the need under varying scenarios.Projections for documented cases were made for varying degree of containment and mitigation strategies.Correspondingly,data on health resources was collated from various government records.Further,we computed daily turnover of each of these resources which was then adjusted for proportion of cases requiring mild,severe and critical care to arrive at maximum number of COVID-19 cases manageable by health care system of India.Findings:Our results revealed pervasive deficits in the capacity of public health system to absorb surge in need during peak of epidemic.Also,model suggests that continuing strict lockdown measures in India after mid-May 2020 would have been ineffective in suppressing total infections significantly.Augmenting testing to 1,500,000 tests per day during projected peak(mid-September)under social-distancing measures and current test to positive rate of 9.7%would lead to more documented cases(60,000,000 to 90,000,000)culminating to surge in demand for hospital resources.A minimum allocation of 13x,70x and 37x times more beds for mild cases,ICU beds and mechanical ventilators respectively would be required to commensurate with need under that scenario.However,if testing capacity is limited to 9,000,000 tests per day(current situation as of 19th August 2020)under continued social-distancing measures,documented cases would plummet significantly,still requiring 5x,31x and 16x times the current allocated resources(beds for mild cases,ICU beds and mechanical ventilators respectively)to meet unmet need for COVID-19 treatment in India.