Predicting COVID-19 fatality rate based on age group using LSTM

Objective: To predict the daily incidence and fatality rates based on long short-term memory (LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran. Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other. Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females (49.7%), and 25 586 were males (50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively; for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.

Predicting COVID-19 fatality rate based on age group using LSTM

Objective: To predict the daily incidence and fatality rates based on long short-term memory (LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran. Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other. Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females (49.7%), and 25 586 were males (50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively; for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.

Effect of postpartum depression on women's mental and physical health four years after childbirth

Background: Postpartum depression has been shown to affect women's health in the long term but no studies have assessed this in the Islamic Republic of Iran.

Aims: This study determined the prevalence of current depression and illness in women who had experienced postpartum depression four years after childbirth, and evaluated the factors associated with current depression.

Methods: In a cohort study in 2009, 1801 pregnant women without depression at 32–42 weeks of pregnancy attending Mazandaran primary healthcare centres were examined for postpartum depression using the Edinburgh Postnatal Depression Scale [EPDS]. After four years, 204 women of the original cohort with postpartum depression and 467 without postpartum depression were again evaluated using the EPDS, and other questionnaires to determine the prevalence of current depression and other health problems. Multivariable logistic regression analysis was used to evaluate the factors associated with current depression and other health problems.

Results: The mean age of the women was 30.13 [SD 5.21] years. Women with postpartum depression were two times more likely to experience depression four years after childbirth [OR = 2.16, 95% CI: 1.38–3.36]. They were also significantly more likely to experience chronic diseases [OR = 2.49, 95% CI: 1.38–4.50] and score higher on the General Health Questionnaire [OR = 2.50, 95% CI: 1.38–4.50].

Conclusions: Postpartum depression predisposes women to later depression and other mental and physical health problems. Women with postpartum depression need to be identified and provided with support and appropriate interventions to avoid later health problems

Physical violence against pregnant women by an intimate partner, and adverse pregnancy outcomes in Mazandaran province, Iran

Violence against women during pregnancy is linked to poor outcome of pregnancy, which is reported to have widespread in Iran. The aim of this study was to determine the prevalence of physical violence against women by an intimate partner during pregnancy, and to assess the impact of this physical violence on pregnancy outcomes. A prospective cohort study was conducted on the characteristics of pregnant women in urban areas and related violence. The modified standard World Health Organization Domestic Violence Questionnaire was used to classify pregnant women and domestic violence. A total of 1461 pregnant women were selected using cluster sampling. The association between sociodemographic with intimate partner violence [IPV] and IPV with pregnancy outcomes was determined using logistic regression. Of these, 206 [14.1%] [confidence interval = 12.3-15.9] reported physical IPV during pregnancy. The adjusted odds ratio for IPV in illiterate women or those with primary level of education [0.001], secondary level education [0.003], and in low income households [0.0001] were significantly higher than in those women with university level education and in higher income households. After adjusting for suspected confounding factors, the women with a history of violence by partners had 1.9 fold risk of premature rupture of membranes, and a 2.9 fold risk of low birth weight compared to women who did not experience any violence from their partners. The results of this research indicated that the prevalence of IPV was high among pregnant women. Therefore, it is necessary to emphasize the screening of pregnant women at Primary Health Centers to prevent physical abuse