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The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach.

ABSTRACT: This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notably, we find no significant effects of business closures. Finally, infections become higher in countries with greater income inequality, higher tourist inflows, poorly educated adults, and weak governance quality. We conclude that several policy interventions reduce infection rates for poorer countries. Further, economic and institutional factors are important; thereby justifying the use, and ultimately success, of economic support to households during the initial infection period.

SUBMITTER: Zamanzadeh A

PROVIDER: S-EPMC9307185 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach.

Zamanzadeh Akbar A Cavoli Tony T

PloS one 20220722 7

This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notab ...[more]

PMID: 35867692

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Project description:IntroductionThe neonatal period is the most vulnerable time in a child's life, contributing to almost half of all deaths in children under 5 years. Many of these deaths are preventable and are mainly caused by preterm birth, birth asphyxia, or serious infections. Over the past decade, the evidence base for interventions to prevent and manage these causes of neonatal mortality and morbidity in low- and middle-income countries (LMICs) has expanded significantly. This growth calls for a comprehensive and systematic approach to synthesizing the available evidence. This paper describes the methodological approach taken before and during the conduct of the systematic overviews and reviews described in the online supplementary material (for all online suppl. material, see <ext-link ext-link-type="doi" xlink:href="https://doi.org/10.1159/000542754" xmlns:xlink="http://www.w3.org/1999/xlink">https://doi.org/10.1159/000542754</ext-link>).MethodsAlongside consultation with a newborn technical advisory group, the overall evidence synthesis approach began with an extensive literature-scoping exercise to establish a universe of interventions that were relevant to neonatal health and survival and to identify the associated systematic reviews examining their effectiveness. Three main approaches were taken to synthesize the evidence based on the availability of prior evidence. New systematic reviews were conducted for topics lacking an existing comprehensive synthesis. Existing systematic reviews with search dates prior to 2020 were updated. High-quality, up-to-date systematic reviews were used without modification. In all cases, trial data from studies conducted in LMICs were sought and prioritized for analysis.ConclusionA comprehensive approach to summarizing the best available evidence for newborn intervention effectiveness is described.IntroductionThe neonatal period is the most vulnerable time in a child's life, contributing to almost half of all deaths in children under 5 years. Many of these deaths are preventable and are mainly caused by preterm birth, birth asphyxia, or serious infections. Over the past decade, the evidence base for interventions to prevent and manage these causes of neonatal mortality and morbidity in low- and middle-income countries (LMICs) has expanded significantly. This growth calls for a comprehensive and systematic approach to synthesizing the available evidence. This paper describes the methodological approach taken before and during the conduct of the systematic overviews and reviews described in the online supplementary material (for all online suppl. material, see <ext-link ext-link-type="doi" xlink:href="https://doi.org/10.1159/000542754" xmlns:xlink="http://www.w3.org/1999/xlink">https://doi.org/10.1159/000542754</ext-link>).MethodsAlongside consultation with a newborn technical advisory group, the overall evidence synthesis approach began with an extensive literature-scoping exercise to establish a universe of interventions that were relevant to neonatal health and survival and to identify the associated systematic reviews examining their effectiveness. Three main approaches were taken to synthesize the evidence based on the availability of prior evidence. New systematic reviews were conducted for topics lacking an existing comprehensive synthesis. Existing systematic reviews with search dates prior to 2020 were updated. High-quality, up-to-date systematic reviews were used without modification. In all cases, trial data from studies conducted in LMICs were sought and prioritized for analysis.ConclusionA comprehensive approach to summarizing the best available evidence for newborn intervention effectiveness is described.

Project description:ImportanceMany randomized clinical trials (RCTs) led by high-income countries (HICs) now enroll patients from lower middle-income countries (LMICs) and upper middle-income countries (UMICs). Although enrolling diverse populations promotes research collaborations, there are issues regarding which countries participate in RCTs and how this participation may contribute to global research.ObjectiveTo describe which UMICs and LMICs participate in RCTs led by HICs.Design, setting, and participantsA cross-sectional study of all oncology RCTs published globally during January 1, 2014, to December 31, 2017, was conducted. The study cohort was restricted to RCTs led by HICs that enrolled participants from LMICs and UMICs. Study analyses were conducted in November 1, 2021, to May 31, 2022.Main outcomes and measuresA bibliometric approach (Web of Science 2007-2017) was used to explore whether RCT participation was proportional to other measures of cancer research activity. Participation in RCTs (ie, percentage of RCTs in the cohort in which each LMIC and UMIC participated) was compared with country-level cancer research bibliometric output (ie, percentage of total cancer research bibliometric output from the same group of countries that came from a specific LMIC and UMIC).ResultsAmong the 636 HIC-led RCTs, 186 trials (29%) enrolled patients in LMICs (n = 84 trials involving 11 LMICs) and/or UMICs (n = 181 trials involving 26 UMICs). The most common participating LMICs were India (42 [50%]), Ukraine (39 [46%]), Philippines (23 [27%]), and Egypt (12 [14%]). The most common participating UMICs were Russia (115 [64%]), Brazil (94 [52%]), Romania (62 [34%]), China (56 [31%]), Mexico (56 [31%]), and South Africa (54 [30%]). Several LMICs are overrepresented in the cohort of RCTs based on proportional cancer research bibliometric output: Ukraine (46% of RCTs but 2% of cancer research bibliometric output), Philippines (27% RCTs, 1% output), and Georgia (8% RCTs, 0.2% output). Overrepresented UMICs include Russia (64% RCTs, 2% output), Romania (34% RCTs, 2% output), Mexico (31% RCTs, 2% output), and South Africa (30% RCTs, 1% output).Conclusions and relevanceIn this cross-sectional study, a substantial proportion of RCTs led by HICs enrolled patients in LMICs and UMICs. The LMICs and UMICs that participated in these trials did not match overall cancer bibliometric output as a surrogate for research ecosystem maturity. Reasons for this apparent discordance and how these data may inform future capacity-strengthening activities require further study.

Dataset Information

The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach.

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The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach.

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