Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Funding Information: M.B.A. holds a Tier 2 Canada Research Chair in the Developmental Origins of Chronic Disease at the University of Manitoba and is a Fellow in the Canadian Institutes for Advanced Research (CIFAR) Humans and the Microbiome Program. Her effort on this project was partly supported by HDR UK and ICODA. K.K.C.M. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G) and grants from C W Maplethorpe Fellowship, National Institute of Health Research UK, European Commission Framework Horizon 2020 and has consulted for IQVIA Ltd. A.S. is supported by ICODA and HDR UK, and has received a research grant from HDR UK to the BREATHE Hub. He participates on the Scottish and UK Government COVID-19 Advisory Committees, unremunerated. S.J.S. is supported by a Wellcome Trust Clinical Career Development Fellowship (209560/Z/17/Z) and HDR UK, and has received personal fees from Hologic and Natera outside the submitted work. D.B. is supported by a National Health and Medical Research Council (Australia) Investigator Grant (GTN1175744). I.C.K.W. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G), and grants from Hong Kong Research Grant Council, National Institute of Health Research UK, and European Commission Framework Horizon 2020. H.Z. is supported by a UNSW Scientia Program Award and reports grants from European Commission Framework Horizon 2020, Icelandic Centre for Research, and Australia’s National Health and Medical Research Council. H.Z. was an employee of the UNSW Centre for Big Data Research in Health, which received funding from AbbVie Australia to conduct research, unrelated to the current study. I.I.A.A., C.D.A., K.A., A.I.A., L.C., S.S., G.E.-G., O.W.G., L. Huicho, S.H., A.K., K.L., V.N., I.P., N.R.R., T.R., T.A.H.R., V.L.S., E.M.S., L.T., R.W. and H.Z. received funding from HDRUK (grant #2020.106) to support data collection for the iPOP study. K.H., R.B., S.O.E., A.R.-P. and J.H. receive salary from ICODA. M.B. received trainee funding from HDRUK (grant #2020.106). J.E.M. received trainee funding from HDRUK (grant #2020.109). Other relevant funding awarded to authors to conduct research for iPOP include: M.G. received funding from THL, Finnish Institute for Health and Welfare to support data collection. K.D. received funding from EDCTP RIA2019 and HDRUK (grant #2020.106) to support data collection. R.B. received funding from Alzheimer’s Disease Data Initiative and ICODA for the development of federated analysis. A.D.M. received funding from HDR UK who receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK, which is funded by the Economic and Social Research Council (grant ES/S007393/1). N.A. received funding from the National Institutes of Health (R35GM138353). O.S received funding from NordForsk (grant #105545). The remaining authors declare no competing interests. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/ ) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Publisher Copyright: © 2023, The Author(s).Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from −90% to +30%, were reported in many countries following early COVID-19 pandemic response measures (‘lockdowns’). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95–0.98, P value <0.0001), second (0.96, 0.92–0.99, 0.03) and third (0.97, 0.94–1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96–1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88–1.14, 0.98), third (0.99, 0.88–1.12, 0.89) and fourth (1.01, 0.87–1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02–1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03–1.15, 0.002), third (1.10, 1.03–1.17, 0.003) and fourth (1.12, 1.05–1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.Peer reviewe

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

The ZIKApp for detection of potential arbovirus infections and pregnancy complications in pregnant women in Jamaica: a pilot study

Background: Evidence of the benefits of mHealth technology including symptom tracking Apps for research, surveillance and prevention is growing, including for arboviruses and for pregnancy interventions. No study has yet addressed arbovirus symptom tracking in pregnancy. Objective: To evaluate the use of a smartphone app (“ZIKApp”) designed to self-report arbovirus symptoms and pregnancy complications, and to assess compliance with daily symptom diaries until the end of pregnancy in a cohort of women in an arbovirus endemic, subtropical, middle-developing country (Jamaica). Methods: Pregnant women aged 16 and over, having a smartphone, and planning on delivering at the recruiting centre were enrolled from an antenatal clinic in February-July 2020. The ZIKApp comprised a daily symptom diary based on algorithms to identify potential episodes of arboviral infection and/or pregnancy complications that triggered automatic notifications to participants. Socio-demographic, epidemiological and obstetric information was collected at enrolment, with additional review of medical records; and users' perception through an exit survey. Descriptive analyses and logistic regression of possible factors associated with diary adherence were performed. Results: Of 173 women enrolled, 90% (157) used ZIKApp for median duration of 155 days between enrolment and pregnancy end, six used the app for 34 years versus those 25-29 (AOR 3.14 95%CI 1.10-8.98) and two-fold higher odds for women with tertiary versus secondary education (AOR 2.26, 95% CI 1.06-4.83). Of 161 women who ever made a diary entry, a total of 5454 individual symptom reports were made (median 17 per woman, max 278). Nine (5.3%) women reported symptom combinations triggering a “potential arbovirus episode” (none had an adverse pregnancy outcome) and 55 (32.9%) women reported painful uterine contractions, or vaginal bleeding, mainly in the month before delivery. The exit survey showed that 52% (71/137) of women rated the App as an excellent experience and were less likely to be poor diary adherers (p=.04); 138/139 women reported that the App was easy to understand and to use. Conclusions: In the era of telemedicine and mHealth, adherence to the ZIKApp in pregnancy was high. The pilot has demonstrated the feasibility and usability of the App in an arbovirus-endemic region, supporting its future development to contribute to surveillance and diagnosis of arboviral infections in pregnancy and promise for implementation by direct treatment and care teams to optimise maternal care

Detection of Potential Arbovirus Infections and Pregnancy Complications in Pregnant Women in Jamaica Using a Smartphone App (ZIKApp): Pilot Evaluation Study

There is growing evidence of the benefits of mobile health technology, which include symptom tracking apps for research, surveillance, and prevention. No study has yet addressed arbovirus symptom tracking in pregnancy

Antenatal Seroprevalence of Zika and Chikungunya Viruses, Kingston Metropolitan Area, Jamaica, 2017-2019

To determine the extent of exposure to Zika virus (ZIKV) and chikungunya virus (CHIKV) in Jamaica, we collected serum from 584 pregnant women during 2017-2019. We found that 15.6% had antibodies against ZIKV and 83.6% against CHIKV. These results indicate potential recirculation of ZIKV but not CHIKV in the near future

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways