Department of Management Studies, Indian Institute of Technology, Madras, Chennai, India.
Department of Computer Science, SRM Institute of Science and Technology, Chengalpattu, Tamil Nadu, India.
PLoS One. 2023 Sep 21;18(9):e0291749. doi: 10.1371/journal.pone.0291749. eCollection 2023.
COVID-19 has impacted the healthcare system across the globe. The study will span three pandemic waves in 2020, 2021, and 2022. The goal is to learn how the pandemic affects antenatal care (ANC) and emergency delivery care for pregnant women in Tamil Nadu, India, and how medical services respond. The study employs counterfactual analysis to evaluate the causal impact of the pandemic. A feedforward in combination with a simple auto-regressive neural network (AR-Net) is used to predict the daily number of calls for ambulance services (CAS). Three categories of the daily CAS count between January 2016 and December 2022 are utilised. The total CAS includes all types of medical emergencies; the second group pertains to planned ANC for high-risk pregnant women and the third group comprises CAS from pregnant women for medical emergencies. The second wave's infection and mortality rates were up to six times higher than the first. The phases in wave-II, post-wave-II, wave-III, and post-wave-III experienced a significant increase in both total IFT (inter-facility transfer) and total non-IFT calls covering all emergencies relative to the counterfactual, as evidenced by reported effect sizes of 1 and a range of 0.65 to 0.85, respectively. This highlights overwhelmed health services. In Tamil Nadu, neither emergency prenatal care nor planned prenatal care was affected by the pandemic. In contrast, the increase in actual emergency-related IFT calls during wave-II, post-wave-II, wave-III, and post-wave-III was 62%, 160%, 141%, and 165%, respectively, relative to the counterfactual. During the same time periods, the mean daily CAS related to prenatal care increased by 47%, 51%, 38%, and 38%, respectively, compared to pre-pandemic levels. The expansion of ambulance services and increased awareness of these services during wave II and the ensuing phases of Covid-19 pandemic have enhanced emergency care delivery for all, including obstetric and neonatal cohorts.
COVID-19 对全球医疗体系造成了影响。本研究将跨越 2020 年、2021 年和 2022 年的三个大流行浪潮。目的是了解大流行如何影响印度泰米尔纳德邦的产前护理 (ANC) 和紧急分娩护理，以及医疗服务如何应对。该研究采用反事实分析来评估大流行的因果影响。前馈与简单的自回归神经网络 (AR-Net) 相结合，用于预测救护车服务 (CAS) 的每日呼叫次数。使用 2016 年 1 月至 2022 年 12 月期间的三类每日 CAS 计数。总 CAS 包括所有类型的医疗紧急情况；第二类是高危孕妇计划 ANC，第三类是孕妇因医疗紧急情况呼叫 CAS。第二波的感染率和死亡率比第一波高六倍。在第二波、第二波后、第三波和第三波后阶段，所有紧急情况的总 IFT（机构间转移）和总非 IFT 呼叫都显著增加，与反事实相比，报告的效应大小分别为 1 和 0.65 至 0.85 的范围。这突显了不堪重负的医疗服务。在泰米尔纳德邦，紧急产前护理和计划产前护理都没有受到大流行的影响。相比之下，第二波、第二波后、第三波和第三波后期间实际与紧急情况相关的 IFT 呼叫增加了 62%、160%、141%和 165%，与反事实相比。在同一时期，与产前护理相关的每日 CAS 平均增加了 47%、51%、38%和 38%，与大流行前水平相比。在第二波和随后的 COVID-19 大流行阶段，救护车服务的扩展和对这些服务的认识提高，增强了所有人的紧急护理服务，包括产科和新生儿群体。
