ABSTRACT
What can we learn about the coronavirus pandemic from text-mining the titles of journal papers? By Samuel R. Neal and Cindy Zheng.
ABSTRACT
OBJECTIVES: To examine indirect impacts of the COVID-19 pandemic on neonatal care in low-income and middle-income countries. DESIGN: Interrupted time series analysis. SETTING: Two tertiary neonatal units in Harare, Zimbabwe and Lilongwe, Malawi. PARTICIPANTS: We included a total of 6800 neonates who were admitted to either neonatal unit from 1 June 2019 to 25 September 2020 (Zimbabwe: 3450; Malawi: 3350). We applied no specific exclusion criteria. INTERVENTIONS: The first cases of COVID-19 in each country (Zimbabwe: 20 March 2020; Malawi: 3 April 2020). PRIMARY OUTCOME MEASURES: Changes in the number of admissions, gestational age and birth weight, source of admission referrals, prevalence of neonatal encephalopathy, and overall mortality before and after the first cases of COVID-19. RESULTS: Admission numbers in Zimbabwe did not initially change after the first case of COVID-19 but fell by 48% during a nurses' strike (relative risk (RR) 0.52, 95% CI 0.41 to 0.66, p<0.001). In Malawi, admissions dropped by 42% soon after the first case of COVID-19 (RR 0.58, 95% CI 0.48 to 0.70, p<0.001). In Malawi, gestational age and birth weight decreased slightly by around 1 week (beta -1.4, 95% CI -1.62 to -0.65, p<0.001) and 300 g (beta -299.9, 95% CI -412.3 to -187.5, p<0.001) and outside referrals dropped by 28% (RR 0.72, 95% CI 0.61 to 0.85, p<0.001). No changes in these outcomes were found in Zimbabwe and no significant changes in the prevalence of neonatal encephalopathy or mortality were found at either site (p>0.05). CONCLUSIONS: The indirect impacts of COVID-19 are context-specific. While our study provides vital evidence to inform health providers and policy-makers, national data are required to ascertain the true impacts of the pandemic on newborn health.
Subject(s)
COVID-19 , Infant Health , Pandemics , COVID-19/epidemiology , Hospital Units , Humans , Infant Health/statistics & numerical data , Infant, Newborn , Interrupted Time Series Analysis , Malawi/epidemiology , Tertiary Care Centers , Zimbabwe/epidemiologyABSTRACT
What can we learn about the coronavirus pandemic from text-mining the titles of journal papers? By Samuel R. Neal and Cindy Zheng