ABSTRACT
BACKGROUND: The World Health Organization released a statement indicating that women can choose to give birth at home if their pregnancy is low risk and they receive the appropriate level of care during labor and childbirth. Additionally, there needs to be a contingency plan for transfer to a prop-erly staffed and equipped birthing unit in case of problems. The Saudi Arabian Ministry of Health "Safe Birth Model of Care” by 2030 aims to have a midwifery-led continuity of maternity care as standard: low-risk births are to take place at home or at a birth center, depending on the preference of the woman and her family. Low-risk pregnant women will be expected to receive antenatal care from an appro-priately trained and experienced primary care physician or midwife, as appropriate, with the option to refer to the comprehensive obstetrics service as necessary. This midwifery-led continuity of care has yet to be implemented in Saudi Arabia (Altaweli et al., 2020). RESEARCH PURPOSES: The purposes of this study were to assess the community of respondents to an online survey and perspectives regarding home birth and determine challenges to initiation of a policy and practice of home birth in Saudi Arabia. METHODS: A cross-sectional design using an online 14-item online survey instrument was used to collect data from 5,930 respondents who provided their views on home birth in Saudi Arabia. FINDINGS: A total of 53.4% of respondents were interested in the concept of home birth, with the COVID-19 pandemic as the reason for this interest in slightly more than one-third of respondents (37.4%). Additionally, 14.3% hoped to avoid unnecessary medical interventions in a hospital setting. It was also found that 46.6% of the respondents were not interested in the potential for a home birth, and of those, 98.8% attributed their disinterest in the safety of hospitals to their preference of a home birth. CONCLUSIONS: There was significant interest in the concept of home birth in Saudi Arabia due to the COVID-19 pandemic and related restrictions. This interest was related to a desire of women to have a more positive birth experience and avoid unnecessary medical interventions. The findings suggest a clear need for a fully developed home birth policy, fully integrated with existing maternity care services in Saudi Arabia, and increased awareness of the safety and suitability of home birth for low-risk women. Home birth should be an option for women with low-risk pregnancies in Saudi Arabia. © 2023, Springer Publishing Company. All rights reserved.
ABSTRACT
Introduction: The health systems needed to improve their learning capacities during the COVID-19 pandemic. Iran is one of the countries massively struck by the pandemic. This study aimed to explore whether and how the policy interventions made by Iran's policymakers at the national level to control COVID-19, could improve the rapid learning characteristics of the health system. Methods: A guide to clarify rapid learning health system (RLHS) characteristics was developed. The guide was used by two independent authors to select the policy interventions that could improve RLHS characteristics, then, to analyze the content of the selected policy interventions. In each stage, results were compared and discussed by all three authors. Final results were presented based on different RLHS characteristics and the potential mechanisms of contribution. Results: Five hundred policy interventions were developed during the first 7 months of the outbreak. Thirty-one policy interventions could potentially improve RLHS characteristics (6.2%). Two characteristics, such as the timely production of research evidence and the appropriate decision support were addressed by selected policy interventions. Policies, that could improve learning capacities, focused on decision-maker groups more than user groups or researcher groups. Conclusions: Most of the developed policy interventions during the first months of the epidemic did not address the learning capacities of the health system. To improve health system functions, improving RLHS characteristics of the health system, especially in patient-centered and data linkage characteristics, is recommended. © 2023 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.
ABSTRACT
Background: Since the start of the global COVID-19 pandemic, countries have been mirroring each other's policies to mitigate the spread of the virus. Whether current measures alone will lead to behavioral change such as social distancing, washing hands, and wearing a facemask is not well understood. The objective of this study is to better understand individual variation in behavioral responses to COVID-19 by exploring the influence of beliefs, motivations and policy measures on public health behaviors. We do so by comparing The Netherlands and Flanders, the Dutch speaking part of Belgium. Methods and findings: Our final sample included 2,637 respondents from The Netherlands and 1,678 from Flanders. The data was nationally representative along three dimensions: age, gender, and household income in both countries. Our key outcome variables of interest were beliefs about policy effectiveness;stated reasons for complying with public rules;and changes in behavior. For control variables, we included a number of measures of how severe the respondent believed Covid-19 to be and a number of negative side effects that the person may have experienced: loneliness, boredom, anxiety, and conflicts with friends and neighbors. Finally, we controlled for socio-demographic factors: age, gender, income (categorical), education (categorical) and the presence of Covid-19 risk factors (diabetes, high blood pressure, heart disease, asthma, allergies). The dependent variable for each of the estimation models is dichotomous, so we used Probit models to predict the probability of engaging in a given behavior. We found that motivations, beliefs about the effectiveness of measures, and pre-pandemic behavior play an important role. The Dutch were more likely to wash their hands than the Flemish (15.4%, p < 0.01), visit family (15.5%, p < .01), run errands (12.0%, p < 0.05) or go to large closed spaces such as a shopping mall (21.2%, p < 0.01). The Dutch were significantly less likely to wear a mask (87.6%, p < 0.01). We also found that beliefs about the virus, psychological effects of the virus, as well as pre-pandemic behavior play a role in adherence to recommendations. Conclusions: Our results suggest that policymakers should consider behavioral motivations specific to their country in their COVID-19 strategies. In addition, the belief that a policy is effective significantly increased the probability of the behavior, so policy measures should be accompanied by public health campaigns to increase adherence. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
BACKGROUND: SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement error and other contaminants. OBJECTIVE: The aim of this study is to provide a proof of concept of the creation of surveillance metrics that correct for measurement error and data contamination to determine when it is safe to ease pandemic restrictions. We applied state-of-the-art statistical modeling to existing internet data to derive the best available estimates of the state-level dynamics of COVID-19 infection in the United States. METHODS: Dynamic panel data (DPD) models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique enables control of various deficiencies in a data set. The validity of the model and statistical technique was tested. RESULTS: A Wald chi-square test of the explanatory power of the statistical approach indicated that it is valid (χ210=1489.84, P<.001), and a Sargan chi-square test indicated that the model identification is valid (χ2946=935.52, P=.59). The 7-day persistence rate for the week of June 27 to July 3 was 0.5188 (P<.001), meaning that every 10,000 new cases in the prior week were associated with 5188 cases 7 days later. For the week of July 4 to 10, the 7-day persistence rate increased by 0.2691 (P=.003), indicating that every 10,000 new cases in the prior week were associated with 7879 new cases 7 days later. Applied to the reported number of cases, these results indicate an increase of almost 100 additional new cases per day per state for the week of July 4-10. This signifies an increase in the reproduction parameter in the contagion models and corroborates the hypothesis that economic reopening without applying best public health practices is associated with a resurgence of the pandemic. CONCLUSIONS: DPD models successfully correct for measurement error and data contamination and are useful to derive surveillance metrics. The opening of America involves two certainties: the country will be COVID-19-free only when there is an effective vaccine, and the "social" end of the pandemic will occur before the "medical" end. Therefore, improved surveillance metrics are needed to inform leaders of how to open sections of the United States more safely. DPD models can inform this reopening in combination with the extraction of COVID-19 data from existing websites.