Healthcare utilization and maternal and child mortality during the COVID-19 pandemic in 18 low- and middle-income countries: An interrupted time-series analysis with mathematical modeling of administrative data

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

The Coronavirus Disease 2019 (COVID-19) pandemic has had wide-reaching direct and indirect impacts on population health. In low- and middle-income countries, these impacts can halt progress toward reducing maternal and child mortality. This study estimates changes in health services utilization during the pandemic and the associated consequences for maternal, neonatal, and child mortality.

Methods and findings

Data on service utilization from January 2018 to June 2021 were extracted from health management information systems of 18 low- and lower-middle-income countries (Afghanistan, Bangladesh, Cameroon, Democratic Republic of the Congo (DRC), Ethiopia, Ghana, Guinea, Haiti, Kenya, Liberia, Madagascar, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Somalia, and Uganda). An interrupted time-series design was used to estimate the percent change in the volumes of outpatient consultations and maternal and child health services delivered during the pandemic compared to projected volumes based on prepandemic trends. The Lives Saved Tool mathematical model was used to project the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions were also correlated to the monthly number of COVID-19 deaths officially reported, time since the start of the pandemic, and relative severity of mobility restrictions. Across the 18 countries, we estimate an average decline in OPD volume of 13.1% and average declines of 2.6% to 4.6% for maternal and child services. We projected that decreases in essential health service utilization between March 2020 and June 2021 were associated with 113,962 excess deaths (110,686 children under 5, and 3,276 mothers), representing 3.6% and 1.5% increases in child and maternal mortality, respectively. This excess mortality is associated with the decline in utilization of the essential health services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, associated with 27.5% of the excess deaths, occurred during the second quarter of 2020, regardless of whether countries reported the highest rate of COVID-19-related mortality during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. The study is limited by the extent to which administrative data, which varies in quality across countries, can accurately capture the changes in service coverage in the population.

Conclusions

Declines in healthcare utilization during the COVID-19 pandemic amplified the pandemic’s harmful impacts on health outcomes and threaten to reverse gains in reducing maternal and child mortality. As efforts and resource allocation toward prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low- and middle-income countries.

Abstract

Tashrik Ahmed and co-workers study health-care use and maternal and child health outcomes across low- and lower-middle-income countries during the COVID-19 pandemic.

Author summary

Why was this study done?

Disruptions to essential health services during the SARS-CoV-2 (COVID-19) pandemic amplify the pandemic’s impact on morbidity and mortality and pose a profound threat to the ability of low- and middle-income countries to achieve Universal Health Coverage (UHC) and the Sustainable Development Goals (SDGs).
While early studies projected mortality based on hypothesized scenarios, this study presents indirect child, neonatal, and maternal mortality projections during the COVID-19 pandemic based on actual service utilization data.
This study adds to multicountry evidence on changes in the utilization of essential health services from low- and middle-income countries.

What did the authors do and find?

We used data on service utilization in 18 countries to estimate the percent change in health services delivered between March 2020 and June 2021, compared to expected levels given prepandemic trends.
The analysis indicates that all countries experienced service disruptions, the largest of which occurred at the pandemic’s start and during months with strict mobility restrictions, regardless of the reported monthly COVID-19 mortality rates, demonstrating variation in the magnitude of disruptions across countries, services, and time.
Using a mathematical model, we project these disruptions are associated with an additional 113,962 deaths among women in children in the 18 countries, representing increases of 3.6% in child mortality and 1.5% in maternal mortality.

What do these findings mean?

The projected excess mortality caused by disruptions to essential health services is smaller than many initial projections, though still comprises a substantial increase in mortality.
There is strong evidence to recommend that context-specific measures to safeguard essential services be integrated into pandemic preparedness and response activities.

Related collections

Most cited references 40

Record: found
Abstract: found
Article: not found

An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

0 comments Cited 4623 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study

Timothy Roberton, Emily Carter, Victoria Chou … (2020)

Summary Background While the COVID-19 pandemic will increase mortality due to the virus, it is also likely to increase mortality indirectly. In this study, we estimate the additional maternal and under-5 child deaths resulting from the potential disruption of health systems and decreased access to food. Methods We modelled three scenarios in which the coverage of essential maternal and child health interventions is reduced by 9·8–51·9% and the prevalence of wasting is increased by 10–50%. Although our scenarios are hypothetical, we sought to reflect real-world possibilities, given emerging reports of the supply-side and demand-side effects of the pandemic. We used the Lives Saved Tool to estimate the additional maternal and under-5 child deaths under each scenario, in 118 low-income and middle-income countries. We estimated additional deaths for a single month and extrapolated for 3 months, 6 months, and 12 months. Findings Our least severe scenario (coverage reductions of 9·8–18·5% and wasting increase of 10%) over 6 months would result in 253 500 additional child deaths and 12 200 additional maternal deaths. Our most severe scenario (coverage reductions of 39·3–51·9% and wasting increase of 50%) over 6 months would result in 1 157 000 additional child deaths and 56 700 additional maternal deaths. These additional deaths would represent an increase of 9·8–44·7% in under-5 child deaths per month, and an 8·3–38·6% increase in maternal deaths per month, across the 118 countries. Across our three scenarios, the reduced coverage of four childbirth interventions (parenteral administration of uterotonics, antibiotics, and anticonvulsants, and clean birth environments) would account for approximately 60% of additional maternal deaths. The increase in wasting prevalence would account for 18–23% of additional child deaths and reduced coverage of antibiotics for pneumonia and neonatal sepsis and of oral rehydration solution for diarrhoea would together account for around 41% of additional child deaths. Interpretation Our estimates are based on tentative assumptions and represent a wide range of outcomes. Nonetheless, they show that, if routine health care is disrupted and access to food is decreased (as a result of unavoidable shocks, health system collapse, or intentional choices made in responding to the pandemic), the increase in child and maternal deaths will be devastating. We hope these numbers add context as policy makers establish guidelines and allocate resources in the days and months to come. Funding Bill & Melinda Gates Foundation, Global Affairs Canada.

0 comments Cited 636 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21

(2022)

Background Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021. Methods All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification. Findings Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5·94 million worldwide, we estimate that 18·2 million (95% uncertainty interval 17·1–19·6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120·3 deaths (113·1–129·3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4·07 million [3·71–4·36]), the USA (1·13 million [1·08–1·18]), Russia (1·07 million [1·06–1·08]), Mexico (798 000 [741 000–867 000]), Brazil (792 000 [730 000–847 000]), Indonesia (736 000 [594 000–955 000]), and Pakistan (664 000 [498 000–847 000]). Among these countries, the excess mortality rate was highest in Russia (374·6 deaths [369·7–378·4] per 100 000) and Mexico (325·1 [301·6–353·3] per 100 000), and was similar in Brazil (186·9 [172·2–199·8] per 100 000) and the USA (179·3 [170·7–187·5] per 100 000). Interpretation The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic. Funding Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom

0 comments Cited 552 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Tashrik Ahmed:

ORCID: https://orcid.org/0000-0002-1359-8705

Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Timothy Roberton: Role: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing

Petra Vergeer: Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing

Peter M. Hansen: Role: SupervisionRole: Writing – review & editing

Michael A. Peters:

ORCID: https://orcid.org/0000-0002-6423-758X

Role: InvestigationRole: Writing – original draftRole: Writing – review & editing

Anthony Adofo Ofosu:

ORCID: https://orcid.org/0000-0003-0226-3069

Role: Data curationRole: ValidationRole: Writing – review & editing

Charles Mwansambo: Role: Data curationRole: ValidationRole: Writing – review & editing

Charles Nzelu: Role: Data curationRole: ValidationRole: Writing – review & editing

Chea Sanford Wesseh: Role: Data curationRole: ValidationRole: Writing – review & editing

Francis Smart: Role: Data curationRole: ValidationRole: Writing – review & editing

Jean Patrick Alfred: Role: Data curationRole: ValidationRole: Writing – review & editing

Mamoutou Diabate: Role: Data curationRole: ValidationRole: Writing – review & editing

Martina Baye: Role: Data curationRole: ValidationRole: Writing – review & editing

Mohamed Lamine Yansane: Role: Data curationRole: ValidationRole: Writing – review & editing

Naod Wendrad:

ORCID: https://orcid.org/0000-0002-1338-976X

Role: Data curationRole: ValidationRole: Writing – review & editing

Nur Ali Mohamud: Role: Data curationRole: ValidationRole: Writing – review & editing

Paul Mbaka: Role: Data curationRole: ValidationRole: Writing – review & editing

Sylvain Yuma: Role: Data curationRole: ValidationRole: Writing – review & editing

Youssoupha Ndiaye: Role: Data curationRole: ValidationRole: Writing – review & editing

Husnia Sadat: Role: Data curationRole: ValidationRole: Writing – review & editing

Helal Uddin: Role: Data curationRole: ValidationRole: Writing – review & editing

Helen Kiarie:

ORCID: https://orcid.org/0000-0003-2048-8173

Role: Data curationRole: ValidationRole: Writing – review & editing

Raharison Tsihory: Role: Data curationRole: ValidationRole: Writing – review & editing

George Mwinnyaa:

ORCID: https://orcid.org/0000-0002-1924-6065

Role: Formal analysisRole: VisualizationRole: Writing – review & editing

Jean de Dieu Rusatira: Role: Data curationRole: ValidationRole: Writing – review & editing

Pablo Amor Fernandez:

ORCID: https://orcid.org/0000-0003-3484-7317

Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – review & editing

Pierre Muhoza:

ORCID: https://orcid.org/0000-0001-8344-1802

Role: Formal analysisRole: InvestigationRole: Writing – review & editing

Prativa Baral:

ORCID: https://orcid.org/0000-0001-5966-0861

Role: Formal analysisRole: InvestigationRole: Writing – review & editing

Salomé Drouard: Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – review & editing

Tawab Hashemi: Role: ConceptualizationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing

Jed Friedman:

ORCID: https://orcid.org/0000-0002-6763-5890

Role: ConceptualizationRole: MethodologyRole: Writing – review & editing

Gil Shapira:

ORCID: https://orcid.org/0000-0002-1138-7269

Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Lars Åke Persson: Role: Academic Editor

Journal

Journal ID (nlm-ta): PLoS Med

Journal ID (iso-abbrev): PLoS Med

Journal ID (publisher-id): plos

Title: PLoS Medicine

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Print): 1549-1277

ISSN (Electronic): 1549-1676

Publication date (Electronic): 30 August 2022

Publication date Collection: August 2022

Volume: 19

Issue: 8

Electronic Location Identifier: e1004070

Affiliations

[1 ] The Global Financing Facility for Women, Children, and Adolescents, Washington, DC, United States of America

[2 ] Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States of America

[3 ] Development Research, The World Bank, Washington, United States of America

[4 ] Ghana Health Service, Accra, Ghana

[5 ] Ministry of Health, Lilongwe, Malawi

[6 ] Federal Ministry of Health, Abuja, Nigeria

[7 ] Ministry of Health, Monrovia, Liberia

[8 ] Ministry of Health and Sanitation, Freetown, Sierra Leone

[9 ] Ministère de la Sante publique et de la population, Port-au-Prince, Haiti

[10 ] Ministère de la Santé et de l’Hygiène Publique, Bamako, Mali

[11 ] Ministére de la Sante Publiqué, Yaoundé, Cameroon

[12 ] Ministère de la Sante, Conakry, Guinea

[13 ] Ministry of Health, Addis-Ababa, Ethiopia

[14 ] Federal Ministry of Health & Human Services, Mogadishu, Somalia

[15 ] Ministry of Health, Kampala, Uganda

[16 ] Ministére de la Sante, Kinshasa, Republique Democratique du Congo

[17 ] Ministere de la santé et de l’action sociale, Dakar, Senegal

[18 ] Ministry of Health and Family Welfare, Dhaka, Bangladesh

[19 ] Ministry of Health, Nairobi, Kenya

[20 ] Ministère de la Sante publique, Antananarivo, Madagascar

London School of Hygiene and Tropical Medicine, UNITED KINGDOM

Author notes

The authors have declared that no competing interests exist.

* E-mail: tahmed13@ 123456worldbank.org

Author information

Tashrik Ahmed https://orcid.org/0000-0002-1359-8705

Michael A. Peters https://orcid.org/0000-0002-6423-758X

Anthony Adofo Ofosu https://orcid.org/0000-0003-0226-3069

Naod Wendrad https://orcid.org/0000-0002-1338-976X

Helen Kiarie https://orcid.org/0000-0003-2048-8173

George Mwinnyaa https://orcid.org/0000-0002-1924-6065

Pablo Amor Fernandez https://orcid.org/0000-0003-3484-7317

Pierre Muhoza https://orcid.org/0000-0001-8344-1802

Prativa Baral https://orcid.org/0000-0001-5966-0861

Jed Friedman https://orcid.org/0000-0002-6763-5890

Gil Shapira https://orcid.org/0000-0002-1138-7269

Article

Publisher ID: PMEDICINE-D-22-00139

DOI: 10.1371/journal.pmed.1004070

PMC ID: 9426906

PubMed ID: 36040910

SO-VID: 8722cae7-5d49-4929-ac5b-1151919e6c71

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 13 January 2022

Date accepted : 6 July 2022

Page count

Figures: 2, Tables: 4, Pages: 20

Funding

The author(s) received no specific funding for this work.

Custom metadata

Data Availability The data underlying this article were provided by and are property of the ministries of health of the eighteen countries participating in the analysis. The data will be shared on reasonable request with permission of the eighteen ministries from gffsecretariat@ 123456worldbank.org .

Outbreaks COVID-19

ScienceOpen disciplines: Medicine

Data availability:

ScienceOpen disciplines: Medicine

Comments

Comment on this article

scite_

Cited by 25

See all cited by

Most referenced authors 1,149

See all reference authors

- Version 1

Healthcare utilization and maternal and child mortality during the COVID-19 pandemic in 18 low- and middle-income countries: An interrupted time-series analysis with mathematical modeling of administrative data

Read this article at

Abstract

Background

Methods and findings

Conclusions

Abstract

Author summary

Why was this study done?

What did the authors do and find?

What do these findings mean?

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 40

An interactive web-based dashboard to track COVID-19 in real time

Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21

Author and article information

Contributors

Journal

Affiliations

Author notes

Author information

Article

History

Page count

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 166

Cited by 25

Most referenced authors 1,149