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      Effect of the COVID-19 Lockdown on Mobile Payments for Maternal Health: Regression Discontinuity Analysis

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          Abstract

          Background

          The COVID-19 pandemic resulted in the unprecedented popularity of digital financial services for contactless payments and government cash transfer programs to mitigate the economic effects of the pandemic. The effect of the pandemic on the use of digital financial services for health in low- and middle-income countries, however, is poorly understood.

          Objective

          This study aimed to assess the effect of the first COVID-19 lockdown on the use of a mobile maternal health wallet, with a particular focus on delineating the age-dependent differential effects, and draw conclusions on the effect of lockdown measures on the use of digital health services.

          Methods

          We analyzed 819,840 person-days of health wallet use data from 3416 women who used health care at 25 public sector primary care facilities and 4 hospitals in Antananarivo, Madagascar, between January 1 and August 27, 2020. We collected data on savings, payments, and voucher use at the point of care. To estimate the effects of the first COVID-19 lockdown in Madagascar, we used regression discontinuity analysis around the starting day of the first COVID-19 lockdown on March 23, 2020. We determined the bandwidth using a data-driven method for unbiased bandwidth selection and used modified Poisson regression for binary variables to estimate risk ratios as lockdown effect sizes.

          Results

          We recorded 3719 saving events, 1572 payment events, and 3144 use events of electronic vouchers. The first COVID-19 lockdown in Madagascar reduced mobile money savings by 58.5% ( P<.001), payments by 45.8% ( P<.001), and voucher use by 49.6% ( P<.001). Voucher use recovered to the extrapolated prelockdown counterfactual after 214 days, while savings and payments did not cross the extrapolated prelockdown counterfactual. The recovery duration after the lockdown differed by age group. Women aged >30 years recovered substantially faster, returning to prelockdown rates after 34, 226, and 77 days for savings, payments, and voucher use, respectively. Younger women aged <25 years did not return to baseline values. The results remained robust in sensitivity analyses using ±20 days of the optimal bandwidth.

          Conclusions

          The COVID-19 lockdown greatly reduced the use of mobile money in the health sector, affecting savings, payments, and voucher use. Savings were the most significantly reduced, implying that the lockdown affected women’s expectations of future health care use. Declines in payments and voucher use indicated decreased actual health care use caused by the lockdown. These effects are crucial since many maternal and child health care services cannot be delayed, as the potential benefits will be lost or diminished. To mitigate the adverse impacts of lockdowns on maternal health service use, digital health services could be leveraged to provide access to telemedicine and enhance user communication with clear information on available health care access options and adherence to safety protocols.

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          Most cited references39

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          • Article: not found

          A modified poisson regression approach to prospective studies with binary data.

          G Zou (2004)
          Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.
            • Record: found
            • Abstract: found
            • Article: not found

            A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)

            COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries' subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare.
              • Record: found
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              • 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

              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.

                Author and article information

                Contributors
                Journal
                JMIR Public Health Surveill
                JMIR Public Health Surveill
                JPH
                JMIR Public Health and Surveillance
                JMIR Publications (Toronto, Canada )
                2369-2960
                2024
                30 July 2024
                : 10
                : e49205
                Affiliations
                [1 ] Global Digital Last Mile Health Research Lab Charité Center for Global Health Charité - Universitätsmedizin Berlin, Germany Berlin Germany
                [2 ] Heidelberg Institute of Global Health Medical Faculty and University Hospital University of Heidelberg Heidelberg Germany
                [3 ] Wolfson Institute of Population Health Queen Mary University of London London United Kingdom
                [4 ] Ministry of Public Health of the Republic of Madagascar Antananarivo Madagascar
                [5 ] Harvard Center for Population and Development Studies Harvard University Cambridge, MA United States
                [6 ] Africa Health Research Institute Mtubatuba South Africa
                Author notes
                Corresponding Author: Samuel Knauss samuel.knauss@ 123456charite.de
                Author information
                https://orcid.org/0000-0002-3046-9075
                https://orcid.org/0009-0005-6118-8793
                https://orcid.org/0009-0006-4478-7126
                https://orcid.org/0009-0006-4581-9943
                https://orcid.org/0000-0002-4182-4212
                https://orcid.org/0000-0002-3393-0840
                Article
                v10i1e49205
                10.2196/49205
                11322714
                39078698
                c5125fa5-cc7d-4221-b00b-b5e3eb1f7d47
                ©Samuel Knauss, Gracia Andriamiadana, Roxane Leitheiser, Zavaniarivo Rampanjato, Till Bärnighausen, Julius Valentin Emmrich. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 30.07.2024.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.

                History
                : 21 May 2023
                : 8 December 2023
                : 24 January 2024
                : 3 May 2024
                Categories
                Original Paper
                Original Paper

                digital health,behavioral surveillance,digital health wallet,mobile money,covid-19,health financing,public health,sub-saharan africa

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