Indirect impacts of the COVID-19 pandemic at two tertiary neonatal units in Zimbabwe and Malawi: an interrupted time series analysis

  1. Simbarashe Chimhuya
  2. Samuel R Neal
  3. Gwen Chimhini
  4. Hannah Gannon
  5. Mario Cortina Borja
  6. Caroline Crehan
  7. Deliwe Nkhoma
  8. Tarisai Chiyaka
  9. Emma Wilson
  10. Tim Hull-Bailey
  11. Felicity Fitzgerald
  12. Msandeni Chiume
  13. Michelle Heys

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Abstract

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.

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  1. Version published to 10.1136/bmjopen-2021-048955
  2. ScreenIT

    SciScore for 10.1101/2021.01.06.21249322: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Outcomes: We evaluated five outcomes: Ethical approval: Research ethics approval was granted by the UCL Research Ethics Committee (17123/001) and ethics committees in Malawi (P.01/20/2909) and Zimbabwe (MRCZ/A/2570) (Appendix 2).
    Consent: The need to obtain informed consent was waived as we collected only pseudonymised data routinely documented for clinical care.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis: Analyses were performed in R version 3.6.3,18 running on RStudio version 1.2.5033.19 First, admission forms were matched with their corresponding outcome form based on the unique identifier generated at admission.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations and future work: Some limitations should be noted. A limitation intrinsic to interrupted time series analysis is the possibility that another event occurred close to the first case of COVID-19 in either country causing spurious observations. Another potential threat to validity is changing data collection practices. For example, overstretched clinicians might not input data into the NeoTree app for all admitted neonates. However, this is unlikely as the NeoTree app is embedded into routine practice at SMCH and KCH and discussions with local collaborators suggest use of the app has continued without issue. The NeoTree app only collects data on neonates admitted to the NNU. Therefore, our analysis does not capture stillbirths or neonatal deaths that occur in the community. It is troubling to see a dramatic fall in admissions in both sites, raising the possibility that many unwell neonates did not attend a health facility and died at home. A recent study found that facility births decreased by over 50% during the lockdown in Nepal, and facility stillbirth and neonatal mortality rates increased significantly.29 The NeoTree research team is currently collecting data on stillbirths at SMCH and KCH, but these data will still only represent stillbirths that occurred in a health facility. Given the COVID-19 pandemic is not over, it will be important to repeat our analysis over the coming months to further examine longer-term trends in neonatal care provision.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2021.01.06.21249322v1 on medRxiv