Health Services and Patient Satisfaction in IRAN during the COVID-19 Pandemic: A Methodology Based on Analytic Hierarchy Process and Artificial Neural Network

Developing a model of public health system strengthening during pandemic of new emerging respiratory diseases for Iran: A protocol study

The objective of this article is to propose a protocol for developing a model for strengthening the public health system in Iran. Currently, there is no clearly articulated model for strengthening public health systems during the pandemic of new emerging respiratory diseases in Iran. The protocol described here aims to: (1) identify components for strengthening public health systems, during the pandemic of new emerging respiratory diseases worldwide, (2) identify components for strengthening Iran's public health system, and (3) design a model for strengthening the public health system in Iran during the pandemic of new emerging respiratory diseases. The protocol proposes three phases. In the first phase, a realistic review will be conducted to identify components for strengthening public health systems worldwide based on six building block framework. In the second phase, a qualitative study will be used to identify components for strengthening public health systems in Iran during the pandemic of new emerging respiratory diseases. In the third phase, an initial model will be designed, and the Delphi technique will be used to finalize the model. Due to fragility and the significant strain that public health systems experienced during the pandemic, it is imperative to introduce a model that strengthens public health systems through some initiatives and strategies and explains the mechanisms by which they operate. A realist review and qualitative study will provide the evidence needed to support the effective implementation of public health interventions, taking into consideration the diverse contexts of these interventions in Iran.

Stillbirth and Preterm Birth During Lockdown Periods in 5 Waves of COVID-19 Pandemic in Northern Iran: A Region-Wide Cohort Study in Mazandaran Province

Introduction

Conflicting reports for preterm birth and stillbirth during the lockdown imposed during the COVID-19 pandemic have emerged. Most of the studies are related to the initial waves of the pandemic.

Objectives

This study aims to evaluate changes in preterm birth and stillbirth rates during various waves of COVID-19 in northern Iran.

Methods

This is a retrospective cohort study to evaluate preterm birth and stillbirth rate based on weight distribution per 1000 live births during lockdown periods in 5 peaks of the COVID-19 pandemic using the regional data registration system at Mazandaran University of Medical Sciences in northern Iran. We compared these rates with the corresponding months 4 years before the pandemic. The odds ratio for the primary outcome was estimated by logistic regression.

Results

We observed an overall increased rate of preterm birth during the pandemic compared to the pre-pandemic period (4.7% vs 2.8%, P < .001). The overall stillbirth rate increased during the COVID-19 pandemic compared to the pre-pandemic period (7.48/1000 vs 5.41/1000, odds ratio: 1.38 [1.21-1.57]). This increase in the rate of stillbirth was significantly observed in the fifth wave of the COVID-19 pandemic (P < .001).

Conclusion

Our study showed that adverse pregnancy outcomes increased during lockdown periods of a global pandemic. Further studies from geographically diverse regions to evaluate different behavior changes during pregnancy and access to prenatal services, and its impact on pregnancy outcomes is recommended.