Disruption Of Non-COVID-19 Health Care In Latin America During The Pandemic: Effects On Health, Lessons For Policy.

COVID-19 had severe direct and indirect effects on health and well-being in Latin America. To understand the extent to which disruptions among non-COVID-19-related health services affected population health, we used administrative data from the period 2015-21 to examine public hospital discharges and mortality for conditions amenable to health care in four Latin American countries: Brazil, Ecuador, Mexico, and Peru. Between March 2020 and December 2021, hospitalization rates for these conditions declined by 28 percent and mortality rates increased by 15 percent relative to prepandemic years. Noncommunicable diseases accounted for 89 percent of this rise in mortality. The poorest states in each country experienced relatively larger increases in mortality. Our results, which focus on the health effects of service disruption, suggest that maintaining health care services in this region during the pandemic could have avoided at least 96,000 deaths. Policies should focus on maintaining essential health care services during emergencies, particularly for patients with noncommunicable diseases, and on minimizing negative consequences by ensuring coordinated and continuous care; leveraging alternative modalities of care, such as telemedicine; broadening the role of nonphysician health care workers; and expanding options for medication delivery.

Impact of the Salud Mesoamerica Initiative on delivery care choices in Guatemala, Honduras, and Nicaragua.

BACKGROUND: The Salud Mesoamérica Initiative (SMI) is a public-private collaboration aimed to improve maternal and child health conditions in the poorest populations of Mesoamerica through a results-based aid mechanism. We assess the impact of SMI on the staffing and availability of equipment and supplies for delivery care, the proportion of institutional deliveries, and the proportion of women who choose a facility other than the one closest to their locality of residence for delivery. METHODS: We used a quasi-experimental design, including baseline and follow-up measurements between 2013 and 2018 in intervention and comparison areas of Guatemala, Nicaragua, and Honduras. We collected information on 8754 births linked to the health facility closest to the mother's locality of residence and the facility where the delivery took place (if attended in a health facility). We fit difference-in-difference models, adjusting for women's characteristics (age, parity, education), household characteristics, exposure to health promotion interventions, health facility level, and country. RESULTS: Equipment, inputs, and staffing of facilities improved after the Initiative in both intervention and comparison areas. After adjustment for covariates, institutional delivery increased between baseline and follow-up by 3.1 percentage points (ß = 0.031, 95% CI -0.03, 0.09) more in intervention areas than in comparison areas. The proportion of women in intervention areas who chose a facility other than their closest one to attend the delivery decreased between baseline and follow-up by 13 percentage points (ß = - 0.130, 95% CI -0.23, - 0.03) more than in the comparison group. CONCLUSIONS: Results indicate that women in intervention areas of SMI are more likely to go to their closest facility to attend delivery after the Initiative has improved facilities' capacity, suggesting that results-based aid initiatives targeting poor populations, like SMI, can increase the use of facilities closest to the place of residence for delivery care services. This should be considered in the design of interventions after the COVID-19 pandemic may have changed health and social conditions.

Performance of passive case detection for malaria surveillance: results from nine countries in Mesoamerica and the Dominican Republic.

BACKGROUND: In malaria elimination settings, available metrics for malaria surveillance have been insufficient to measure the performance of passive case detection adequately. An indicator for malaria suspected cases with malaria test (MSCT) is proposed to measure the rate of testing on persons presenting to health facilities who satisfy the definition of a suspected malaria case. This metric does not rely on prior knowledge of fever prevalence, seasonality, or external denominators, and can be used to compare detection rates in suspected cases within and between countries, including across settings with different levels of transmission. METHODS: To compute the MSCT, an operational definition for suspected malaria cases was established, including clinical and epidemiological criteria. In general, suspected cases included: (1) persons with fever detected in areas with active malaria transmission; (2) persons with fever identified in areas with no active transmission and travel history to, or residence in areas with active transmission (either national or international); and (3) persons presenting with fever, chills and sweating from any area. Data was collected from 9 countries: Belize, Colombia (in areas with active transmission), Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Nicaragua, and Panama (September-March 2020). A sample of eligible medical records for 2018 was selected from a sample of health facilities in each country. An algorithm was constructed to assess if a malaria test was ordered or performed for cases that met the suspected case definition. RESULTS: A sample of 5873 suspected malaria cases was obtained from 239 health facilities. Except for Nicaragua and Colombia, malaria tests were requested in less than 10% of all cases. More cases were tested in areas with active transmission than areas without cases. Travel history was not systematically recorded in any country. CONCLUSIONS: A statistically comparable, replicable, and standardized metric was proposed to measure suspected malaria cases with a test (microscopy or rapid diagnostic test) that enables assessing the performance of passive case detection. Cross-country findings have important implications for malaria and infectious disease surveillance, which should be promptly addressed as countries progress towards malaria elimination. Local and easy-to-implement tools could be implemented to assess and improve passive case detection.