The prevalence of mental ill-health in women during pregnancy and after childbirth during the Covid-19 pandemic: a Systematic Review and Meta- analysis (preprint)

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) is a respiratory disease which causes coronavirus and has given rise to the Middle East Respiratory Syndrome (MERS), SARS-CoV in Hong Kong and SARS-CoV-2 (COVID-19). COVID-19, to date, has had the highest morbidity and mortality rates globally, thus reaching the pandemic status. Whilst research has explored the impact of pandemic on general wellbeing, there appears to be a paucity on its association with women’s mental health, with many pregnant women reporting the pandemic negatively impacted their mental health. This study aims to explore the prevalence of the impact of the COVID-19, MERS and SARS pandemics on the mental health of pregnant women. A study protocol was developed and published in PROSPERO (CRD42021235356) to explore several key objectives. A literature search was carried out and identified 316 studies. A meta-analysis was conducted to report the findings. There were no studies reporting the mental health impact due to MERS and SARS. Results showed that women who were pregnant or had just given birth displayed various symptoms of poor mental health including those relating to depression (24.9%), anxiety (32.8%), stress (29.44%), Post Traumatic Stress Disorder (PTSD) (27.93%), and sleep disorders (24.38%) during the COVID-19 pandemic. The importance of managing mental health during pregnancy and after-delivery improves the quality of life and wellbeing of mothers hence developing an evidence-based approached as part of pandemic preparedness would improve mental health during challenging times.  

The prevalence of mental ill-health in women during pregnancy and after childbirth during the Covid-19 pandemic: a Systematic review and Meta-analysis (preprint)

Background Severe Acute Respiratory Syndrome Coronavirus (SARSCoV) is a respiratory disease causing coronavirus. SARSCoV has caused the Middle East Respiratory Syndrome (MERS), SARSCoV in Hong King and SARSCoV2 (COVID19). COVID19, to date, have had the highest mortality and morbidity globally, thus reaching the pandemic status. In comparison to research conducted to explore the impact of pandemics on the general wellbeing, there appears to be a paucity on its association with womens mental health. Many pregnant women have reported that the pandemic negatively impacted their mental health. Aim This study aimed is to explore the prevalence of the impact of the COVID19, MERS and SARS pandemics on the mental health of pregnant women. Method A study protocol was developed and published in PROSPERO (CRD42021235356) to explore a number of key objectives. For the purpose of this study PubMed, Science direct, Ovid PsycINFO and EMBASE databases were searched from December 2000 to July 2021. The search results were screened, first by title, and then by abstract. A metaanalysis was conducted to report the findings. Results There were no studies reporting the mental health impact due to MERS and SARS. We systematically identified 316 studies that reported on the mental health of women that were pregnant and soon after birth. The metaanalysis indicated 24.9% (21.37% to 29.02%) of pregnant women reported symptoms of depression, 32.8% (29.05% to 37.21%) anxiety, 29.44% (18.21% to 47.61%) stress, 27.93% (9.05%to 86.15 %) PTSD, and 24.38% (11.89% to 49.96%) sleep disorders during the COVID19 pandemic. Furthermore, the I2 test showed a high heterogeneity value. Conclusion The importance of managing the mental health during pregnancy and after delivery improves the quality of life and wellbeing of mothers. Developing an evidence based mental health framework as part of pandemic preparedness to help pregnant women would improve the quality of care received during challenging times. Keywords: Covid19, Mental ill health, Depression, Anxiety, Stress, Pregnancy, Antenatal care, Postnatal care, Wellbeing

Cervical cancer and COVID-an assessment of the initial effect of the pandemic and subsequent projection of impact for women in England: A cohort study.

OBJECTIVE: To review the effect of the COVID-19 pandemic on the diagnosis of cervical cancer and model the impact on workload over the next 3 years. DESIGN: A retrospective, control, cohort study. SETTING: Six cancer centres in the North of England representing a combined population of 11.5 million. METHODS: Data were collected retrospectively for all diagnoses of cervical cancer during May-October 2019 (Pre-COVID cohort) and May-October 2020 (COVID cohort). Data were used to generate tools to forecast case numbers for the next 3 years. MAIN OUTCOME MEASURES: Histology, stage, presentation, onset of symptoms, investigation and type of treatment. Patients with recurrent disease were excluded. RESULTS: 406 patients were registered across the study periods; 233 in 2019 and 173 in 2020, representing a 25.7% (n = 60) reduction in absolute numbers of diagnoses. This was accounted for by a reduction in the number of low stage cases (104 in 2019 to 77 in 2020). Adding these data to the additional cases associated with a temporary cessation in screening during the pandemic allowed development of forecasts, suggesting that over the next 3 years there would be 586, 228 and 105 extra cases of local, regional and distant disease, respectively, throughout England. Projection tools suggest that increasing surgical capacity by two or three cases per month per centre would eradicate this excess by 12 months and 7 months, respectively. CONCLUSIONS: There is likely to be a significant increase in cervical cancer cases presenting over the next 3 years. Increased surgical capacity could mitigate this with little increase in morbidity or mortality. TWEETABLE ABSTRACT: Covid will result in 919 extra cases of cervical cancer in England alone. Effects can be mitigated by increasing surgical capacity.

Cervical Cancer and COVID: A collaborative assessment of the effect of the COVID pandemic on the presentation of Cervical cancer in the North of England (preprint)

Objective: To review the effect of the COVID-19 pandemic on the presentation of Cervical cancer. Design/ Setting: Retrospective study involving the Regional Cancer Centres in the M62 Group. Methods: Data was collected for two equal time periods. All cervical cancers were included and FIGO 2018 staging was used for the data collection. P values were calculated using binomial hypothesis test for the difference in staging. Time from symptoms to diagnosis was assessed using a normal distribution test. All other calculations were performed using chi-squared test. Statistical significance was considered if p values were <0.05. Main outcome measures: Histology, stage at diagnosis, date of onset of symptoms, investigation and type of treatment. Results: A total of 406 cases of cervical cancer were reviewed; 233 from May – October 2019 (pre-COVID) and 173 between May – October 2020 (post COVID); representing a significant reduction in new cervical cancer diagnoses of 25% post COVID (p<0.001) There was a 42% increase in the delay from start of symptoms to diagnosis Post COVID. Pre COVID, 27% of patients presented with Stage 3 or 4 disease, whilst during COVID this was 38%; statistically significant (p <0.001). When we evaluated the treatments received between the two time periods, this was also statistically significant (chi-squared, p=0.0005). Conclusions: This study has demonstrated a statistically significant increase in the stage of cervical cancer at diagnosis and a change in treatment for cervical cancer following the onset of COVID-19. The implications of this are discussed.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic (preprint)

Pandemic scenarios like SARS-Cov-2 require rapid information aggregation. In the age of eHealth and data-driven medicine, publicly available symptom tracking tools offer efficient and scalable means of collecting and analyzing large amounts of data. As a result, information gains can be communicated to front-line providers. We have developed such an application in less than a month and reached more than 500 thousand users within 48 hours. The dataset contains information on basic epidemiological parameters, symptoms, risk factors and details on previous exposure to a COVID-19 patient. Exploratory Data Analysis revealed different symptoms reported by users with confirmed contacts vs. no confirmed contacts. The symptom combination of anosmia, cough and fatigue was the most important feature to differentiate the groups, while single symptoms such as anosmia, cough or fatigue alone were not sufficient. A linear regression model from the literature using the same symptom combination as features was applied on all data. Predictions matched the regional distribution of confirmed cases closely across Germany, while also indicating that the number of cases in northern federal states might be higher than officially reported. In conclusion, we report that symptom combinations anosmia, fatigue and cough are most likely to indicate an acute SARS-CoV-2 infection.

Emergency calls are early indicators of ICU bed requirement during the COVID-19 epidemic A retrospective study in Ile-de-France region, France (preprint)

Background: The aim of our retrospective study was to evaluate the earliest COVID19-related signal to anticipate requirements of intensive care unit (ICU) beds. Although the number of ICU beds is crucial during the COVID-19 epidemic, there is no recognized early indicator to anticipate it. Methods: In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient, depending on the number of days the indicator has been shifted. Primary endpoint was the number of ICU patients. Results: EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. Conclusion: The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19 or decide additional social measures.