{"id":{"repo_id":"sask","oai_identifier":"oai:harvest.usask.ca:10388/14665"},"canonical_url":"https://search.dev.ndltd.org/etd/sask/oai:harvest.usask.ca:10388/14665","repository":{"repo_id":"sask","name":"University of Saskatchewan","base_url":"https://harvest.usask.ca/server/oai/request"},"display":{"title":"ESTIMATING THE INDIRECT IMPACT OF THE COVID-19 PANDEMIC ON NEONATAL MORTALITY IN NEPAL","abstract":"Background: The unprecedented impacts of the coronavirus disease 2019 pandemic on the utilization of maternal, newborn, and child health services tested the resilience of health systems globally, including Nepal. Lives Saved Tool (LiST) has been used to provide early estimates of maternal and child mortality impact from different scenarios of disruption of routine health services during the pandemic in low- and middle-income countries. Early in the pandemic, reports from Nepal suggested a decrease in the institutional delivery rate and an increase in the institutional neonatal mortality rate. This study aimed to estimate the population-level impact of the pandemic on neonatal mortality in Nepal. Objectives: We aimed to estimate the number of additional neonatal lives saved in Nepal based on the change in pregnancy and childbirth intervention coverage during the pandemic. We also aimed to track the neonatal mortality rate during and after the pandemic against the national targets. In addition, we aimed to visualize priority interventions and cost for scaling up to universal coverage. Methods: We used LiST, a linear deterministic mathematical model, to compare the projection of the number of 'additional' neonatal lives saved in a year and neonatal mortality rate (NMR) based on the reported coverage scenario (per national annual reports) versus the 'target’ coverage scenario (linearly interpolated from pre-pandemic baseline to Nepal Every Newborn Action Plan target). The coverage of four or more antenatal visits and institutional delivery was used as a proxy to LiST pregnancy and childbirth interventions impacting cause-specific neonatal mortality, assuming no change in coverage of other interventions in the model. We used Missed Opportunity Tool, a visualization tool incorporated within the LiST, to identify top interventions at childbirth that prevent additional neonatal deaths, along with the cost of intervention, when scaled up from baseline coverage to 90% in the next year. Results: The LiST projection of the number of additional neonatal lives saved in the projection year 2021 was significantly lower (91; 95% CI 63,128) based on the scenario of ‘reported’ intervention coverage compared to the ‘target’ coverage scenario (247;95% CI 169,350). The projected NMR fell off track in 2021 from 2020, with the estimated NMR (per 1000 livebirths) increasing from 21.31 to 21.39 in the ‘reported’ coverage scenario rather than the expected decrease from 21.32 to 21.12 in the ‘target’ coverage scenario. When scaled up from the current coverage rate to universal coverage, assisted vaginal delivery, cesarian delivery, and neonatal resuscitation would prevent the most neonatal deaths. And neonatal resuscitation could be scaled-up at the lowest cost for neonatal deaths prevented. Conclusion: Lives Saved Tool projection of cause-specific neonatal mortality based on the change in coverage of selected pregnancy and childbirth interventions provided indirect evidence that the pandemic may have adversely impacted the trajectory of neonatal survival in Nepal. Prioritizing the scale-up of childbirth interventions, particularly neonatal resuscitation, to universal coverage offers the best potential to prevent additional neonatal deaths.","abstract_html":"Background: The unprecedented impacts of the coronavirus disease 2019 pandemic on the utilization of maternal, newborn, and child health services tested the resilience of health systems globally, including Nepal. Lives Saved Tool (LiST) has been used to provide early estimates of maternal and child mortality impact from different scenarios of disruption of routine health services during the pandemic in low- and middle-income countries. Early in the pandemic, reports from Nepal suggested a decrease in the institutional delivery rate and an increase in the institutional neonatal mortality rate. This study aimed to estimate the population-level impact of the pandemic on neonatal mortality in Nepal. Objectives: We aimed to estimate the number of additional neonatal lives saved in Nepal based on the change in pregnancy and childbirth intervention coverage during the pandemic. We also aimed to track the neonatal mortality rate during and after the pandemic against the national targets. In addition, we aimed to visualize priority interventions and cost for scaling up to universal coverage. Methods: We used LiST, a linear deterministic mathematical model, to compare the projection of the number of 'additional' neonatal lives saved in a year and neonatal mortality rate (NMR) based on the reported coverage scenario (per national annual reports) versus the 'target’ coverage scenario (linearly interpolated from pre-pandemic baseline to Nepal Every Newborn Action Plan target). The coverage of four or more antenatal visits and institutional delivery was used as a proxy to LiST pregnancy and childbirth interventions impacting cause-specific neonatal mortality, assuming no change in coverage of other interventions in the model. We used Missed Opportunity Tool, a visualization tool incorporated within the LiST, to identify top interventions at childbirth that prevent additional neonatal deaths, along with the cost of intervention, when scaled up from baseline coverage to 90% in the next year. Results: The LiST projection of the number of additional neonatal lives saved in the projection year 2021 was significantly lower (91; 95% CI 63,128) based on the scenario of ‘reported’ intervention coverage compared to the ‘target’ coverage scenario (247;95% CI 169,350). The projected NMR fell off track in 2021 from 2020, with the estimated NMR (per 1000 livebirths) increasing from 21.31 to 21.39 in the ‘reported’ coverage scenario rather than the expected decrease from 21.32 to 21.12 in the ‘target’ coverage scenario. When scaled up from the current coverage rate to universal coverage, assisted vaginal delivery, cesarian delivery, and neonatal resuscitation would prevent the most neonatal deaths. And neonatal resuscitation could be scaled-up at the lowest cost for neonatal deaths prevented. Conclusion: Lives Saved Tool projection of cause-specific neonatal mortality based on the change in coverage of selected pregnancy and childbirth interventions provided indirect evidence that the pandemic may have adversely impacted the trajectory of neonatal survival in Nepal. Prioritizing the scale-up of childbirth interventions, particularly neonatal resuscitation, to universal coverage offers the best potential to prevent additional neonatal deaths.","abstract_has_math":false,"creators":["Dharel, Dinesh"],"institution":"University of Saskatchewan","degree_name":"Master of Science (M.Sc.)","degree_level":"Masters","degree_discipline":"Community and Population Health Science","degree_department":null,"school":null,"contributors":[],"advisors":["Muhajarine, Nazeem"],"committee_chairs":[],"committee_members":["Paudel, Deepak","Pahwa, Punam","Brockway, Meredith"],"year":2023,"date_issued":"2023-05-09","date_published":"2023-05-09","updated_at":"2026-07-24T04:27:16Z","subjects":["Lives Saved Tool","additional neonatal lives saved","Missed Opportunity Tool","cause-specific neonatal mortality","antenatal care","institutional delivery","utilization of MNCH services","Nepal"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10388/14665","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Muhajarine, Nazeem"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Paudel, Deepak","Pahwa, Punam","Brockway, Meredith"]},{"key":"dc:creator","label":"Author","values":["Dharel, Dinesh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-05-09T21:25:23Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-05-09"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Community and Population Health Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (M.Sc.)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Saskatchewan"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Lives Saved Tool","additional neonatal lives saved","Missed Opportunity Tool","cause-specific neonatal mortality","antenatal care","institutional delivery","utilization of MNCH services","Nepal"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10388/14665"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Background: The unprecedented impacts of the coronavirus disease 2019 pandemic on the utilization of maternal, newborn, and child health services tested the resilience of health systems globally, including Nepal. Lives Saved Tool (LiST) has been used to provide early estimates of maternal and child mortality impact from different scenarios of disruption of routine health services during the pandemic in low- and middle-income countries. Early in the pandemic, reports from Nepal suggested a decrease in the institutional delivery rate and an increase in the institutional neonatal mortality rate. This study aimed to estimate the population-level impact of the pandemic on neonatal mortality in Nepal. Objectives: We aimed to estimate the number of additional neonatal lives saved in Nepal based on the change in pregnancy and childbirth intervention coverage during the pandemic. We also aimed to track the neonatal mortality rate during and after the pandemic against the national targets. In addition, we aimed to visualize priority interventions and cost for scaling up to universal coverage. Methods: We used LiST, a linear deterministic mathematical model, to compare the projection of the number of 'additional' neonatal lives saved in a year and neonatal mortality rate (NMR) based on the reported coverage scenario (per national annual reports) versus the 'target’ coverage scenario (linearly interpolated from pre-pandemic baseline to Nepal Every Newborn Action Plan target). The coverage of four or more antenatal visits and institutional delivery was used as a proxy to LiST pregnancy and childbirth interventions impacting cause-specific neonatal mortality, assuming no change in coverage of other interventions in the model. We used Missed Opportunity Tool, a visualization tool incorporated within the LiST, to identify top interventions at childbirth that prevent additional neonatal deaths, along with the cost of intervention, when scaled up from baseline coverage to 90% in the next year. Results: The LiST projection of the number of additional neonatal lives saved in the projection year 2021 was significantly lower (91; 95% CI 63,128) based on the scenario of ‘reported’ intervention coverage compared to the ‘target’ coverage scenario (247;95% CI 169,350). The projected NMR fell off track in 2021 from 2020, with the estimated NMR (per 1000 livebirths) increasing from 21.31 to 21.39 in the ‘reported’ coverage scenario rather than the expected decrease from 21.32 to 21.12 in the ‘target’ coverage scenario. When scaled up from the current coverage rate to universal coverage, assisted vaginal delivery, cesarian delivery, and neonatal resuscitation would prevent the most neonatal deaths. And neonatal resuscitation could be scaled-up at the lowest cost for neonatal deaths prevented. Conclusion: Lives Saved Tool projection of cause-specific neonatal mortality based on the change in coverage of selected pregnancy and childbirth interventions provided indirect evidence that the pandemic may have adversely impacted the trajectory of neonatal survival in Nepal. Prioritizing the scale-up of childbirth interventions, particularly neonatal resuscitation, to universal coverage offers the best potential to prevent additional neonatal deaths."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["ESTIMATING THE INDIRECT IMPACT OF THE COVID-19 PANDEMIC ON NEONATAL MORTALITY IN NEPAL"]}]}],"canonical_facts":{"dc:contributor.advisor":["Muhajarine, Nazeem"],"dc:contributor.committeemember":["Paudel, Deepak","Pahwa, Punam","Brockway, Meredith"],"dc:creator":["Dharel, Dinesh"],"dc:date.accessioned":["2023-05-09T21:25:23Z"],"dc:date.issued":["2023-05-09"],"dc:description.abstract":["Background: The unprecedented impacts of the coronavirus disease 2019 pandemic on the utilization of maternal, newborn, and child health services tested the resilience of health systems globally, including Nepal. Lives Saved Tool (LiST) has been used to provide early estimates of maternal and child mortality impact from different scenarios of disruption of routine health services during the pandemic in low- and middle-income countries. Early in the pandemic, reports from Nepal suggested a decrease in the institutional delivery rate and an increase in the institutional neonatal mortality rate. This study aimed to estimate the population-level impact of the pandemic on neonatal mortality in Nepal. Objectives: We aimed to estimate the number of additional neonatal lives saved in Nepal based on the change in pregnancy and childbirth intervention coverage during the pandemic. We also aimed to track the neonatal mortality rate during and after the pandemic against the national targets. In addition, we aimed to visualize priority interventions and cost for scaling up to universal coverage. Methods: We used LiST, a linear deterministic mathematical model, to compare the projection of the number of 'additional' neonatal lives saved in a year and neonatal mortality rate (NMR) based on the reported coverage scenario (per national annual reports) versus the 'target’ coverage scenario (linearly interpolated from pre-pandemic baseline to Nepal Every Newborn Action Plan target). The coverage of four or more antenatal visits and institutional delivery was used as a proxy to LiST pregnancy and childbirth interventions impacting cause-specific neonatal mortality, assuming no change in coverage of other interventions in the model. We used Missed Opportunity Tool, a visualization tool incorporated within the LiST, to identify top interventions at childbirth that prevent additional neonatal deaths, along with the cost of intervention, when scaled up from baseline coverage to 90% in the next year. Results: The LiST projection of the number of additional neonatal lives saved in the projection year 2021 was significantly lower (91; 95% CI 63,128) based on the scenario of ‘reported’ intervention coverage compared to the ‘target’ coverage scenario (247;95% CI 169,350). The projected NMR fell off track in 2021 from 2020, with the estimated NMR (per 1000 livebirths) increasing from 21.31 to 21.39 in the ‘reported’ coverage scenario rather than the expected decrease from 21.32 to 21.12 in the ‘target’ coverage scenario. When scaled up from the current coverage rate to universal coverage, assisted vaginal delivery, cesarian delivery, and neonatal resuscitation would prevent the most neonatal deaths. And neonatal resuscitation could be scaled-up at the lowest cost for neonatal deaths prevented. Conclusion: Lives Saved Tool projection of cause-specific neonatal mortality based on the change in coverage of selected pregnancy and childbirth interventions provided indirect evidence that the pandemic may have adversely impacted the trajectory of neonatal survival in Nepal. Prioritizing the scale-up of childbirth interventions, particularly neonatal resuscitation, to universal coverage offers the best potential to prevent additional neonatal deaths."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10388/14665"],"dc:language.iso":["en"],"dc:subject":["Lives Saved Tool","additional neonatal lives saved","Missed Opportunity Tool","cause-specific neonatal mortality","antenatal care","institutional delivery","utilization of MNCH services","Nepal"],"dc:title":["ESTIMATING THE INDIRECT IMPACT OF THE COVID-19 PANDEMIC ON NEONATAL MORTALITY IN NEPAL"],"dc:type":["Thesis"],"thesis:degree_discipline":["Community and Population Health Science"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science (M.Sc.)"],"thesis:institution_name":["University of Saskatchewan"]},"updated_at":"2026-07-24T04:27:16Z"}