Effect of COVID-19 on hospital visits in Ningbo, China: an interrupted time-series analysis.
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ABSTRACT: Objective
Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China.Methods
We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models.Results
Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%).Conclusions
Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.
SUBMITTER: Yang ZM
PROVIDER: S-EPMC8135444 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Abstract Objectives This study aims to evaluate the effect of the COVID‐19 pandemic on the frequency of emergency department (ED) visits in Portugal between March 2020 and July 2021. Methods We used data on the monthly number of visits for all public hospitals’ EDs from mainland Portugal between January 2017 and July 2021. We studied the impact of the pandemic overall, by type of ED (general, pediatric, and obstetric) and by Manchester Triage System color (red, orange, yellow, green, and blue) using an interrupted time series analysis. The prepandemic period corresponded to the months from January 2017 to February 2020 and the pandemic period to the months from March 2020 to July 2021. Results We observed over 26 million ED visits, the majority in general EDs (74.0%) and triaged yellow (48.4%) or green (38.4%). During the pandemic period, ED visits decreased 45.7% (95% confidence interval [CI]: –39.8% to –51.2%) and pediatric ED visits decreased by 72.4% (95% CI: –64.6% to –78.6%). A decrease was observed for all colors but tended to be progressively smaller as the priority increased. There was an increase in ED visits during the pandemic period (2.3%; 95% CI: 1.4% to 3.2%), eventually returning to prepandemic values. Conclusion Our data indicate a considerable and long‐lasting effect of the COVID‐19 pandemic affecting mainly pediatric and milder cases, which were returning toward prepandemic values as the pandemic progressed. In a country with frequent use of EDs, the health system may need to be prepared to respond to prepandemic baseline ED demand, together with additional demand because of long‐term sequels of COVID‐19 cases and delayed care for chronic and acute conditions.
| S-EPMC9833280 | biostudies-literature
Project description:BackgroundThere is widespread concern over the impact of public health measures, such as lockdowns, associated with COVID-19 on mental health, including suicide. High-quality evidence from low-income and middle-income countries, where the burden of suicide and self-harm is greatest, is scarce. We aimed to determine the effect of the pandemic on hospital presentations for self-poisoning.MethodsIn this interrupted time-series analysis, we established a new self-poisoning register at the tertiary care Teaching Hospital Peradeniya in Sri Lanka, a lower-middle-income country. Using a standard extraction sheet, data were gathered for all patients admitted to the Toxicology Unit with self-poisoning between Jan 1, 2019, and Aug 31, 2020. Only patients classified by the treating clinician as having intentionally self-poisoned were included. Data on date of admission, age or date of birth, sex, and poisoning method were collected. No data on ethnicity were available. We used interrupted time-series analysis to calculate weekly hospital admissions for self-poisoning before (Jan 1, 2019-March 19, 2020) and during (March 20-Aug 31, 2020) the pandemic, overall and by age (age <25 years vs ≥25 years) and sex. Individuals with missing date of admission were excluded from the main analysis.FindingsBetween Jan 1, 2019, and Aug 31, 2020, 1401 individuals (584 [41·7%] males, 761 [54·3%] females, and 56 [4·0%] of unknown sex) presented to the hospital with self-poisoning and had date of admission data. A 32% (95% CI 12-48) reduction in hospital presentations for self-poisoning in the pandemic period compared with pre-pandemic trends was observed (rate ratio 0·68, 95% CI 0·52-0·88; p=0·0032). We found no evidence that the impact of the pandemic differed by sex (rate ratio 0·64, 95% CI 0·44-0·94, for females vs 0·85, 0·57-1·26, for males; pinteraction=0·43) or age (0·64, 0·44-0·93, for patients aged <25 years vs 0·81, 0·57-1·16, for patients aged ≥25 years; pinteraction=0·077).InterpretationThis is the first study from a lower-middle-income country to estimate the impact of the pandemic on self-harm (non-fatal) accounting for underlying trends. If the fall in hospital presentations during the pandemic reflects a reduction in the medical treatment of people who have self-poisoned, rather than a true fall in incidence, then public health messages should emphasise the importance of seeking help early.FundingElizabeth Blackwell Institute University of Bristol, Wellcome Trust, and Centre for Pesticide Suicide Prevention.TranslationsFor the Sinhalese and Tamil translations of the abstract see Supplementary Materials section.
| S-EPMC8445699 | biostudies-literature
Project description:BackgroundThe unprecedented coronavirus disease 2019 (COVID-19) pandemic has caused millions of infections worldwide and represents a significant challenge facing modern health care systems. This study was conducted to investigate the impact of lockdown measures in a tertiary Children's Hospital in southwest China, which might be used to predict long-term effects related to health-seeking behavior of parents/caregivers.MethodsThis study included newborns enrolled over a span of 86 weeks between January 4, 2019, and August 27, 2020. We designated two time periods for analysis purposes: a stable pre-COVID period(55 weeks between January 4, 2019, and January 23, 2020) and a COVID-impacted period (31 weeks between January 24, 2020, and August 27, 2020). An interrupted time-series analysis was employed to compare changes and trends in hospital admissions and disease spectra before and after the period of nonpharmaceutical interventions (NPIs). Furthermore, this study was conducted to evaluate whether the health-seeking behavior of parents/caregivers was influenced by pandemic factors.ResultsOverall, 16,640 infants were admitted to the neonatology department during the pre-COVID period (n = 12,082) and the COVID-impacted period (n = 4,558). The per week neonatal admissions consistently decreased following the first days of NPIs (January 24, 2020). The average weekly admission rates of 220/week pre-COVID period and 147/week COVID-impacted period. There was an evident decrease in the volume of admissions for all disease spectra after the intervention, whereas the decrease of patients complaining about pathological jaundice-related conditions was statistically significant (p<0.05). In the COVID-impacted period, the percentage of patients who suffered from respiratory system diseases, neonatal encephalopathy, and infectious diseases decreased, while the percentage of pathological jaundice-related conditions and gastrointestinal system diseases increased. The neonatal mortality rates (NMRs) increased by 8.7% during the COVID-impacted period compared with the pre-COVID period.ConclusionsIn summary, there was a significant decline in neonatal admissions in a tertiary care hospital during the COVID-19 Pandemic and the associated NPIs. Additionally, this situation had a remarkable impact on disease spectra and health-seeking behavior of parents/caregivers. We, therefore, advise continuing follow-ups and monitoring the main health indicators in vulnerable populations affected by this Pandemic over time.
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Project description:BackgroundUncontrolled infection and lockdown measures introduced in response have resulted in an unprecedented challenge for health systems internationally. Whether such unprecedented impact was due to lockdown itself and recedes when such measures are lifted is unclear. We assessed the short- and medium-term impacts of the first lockdown measures on hospital care for tracer non-COVID-19 conditions in England, Scotland and Wales across diseases, sexes, and socioeconomic and ethnic groups.MethodsWe used OpenSAFELY (for England), EAVEII (Scotland), and SAIL Databank (Wales) to extract weekly hospital admission rates for cancer, cardiovascular and respiratory conditions (excluding COVID-19) from the pre-pandemic period until 25/10/2020 and conducted a controlled interrupted time series analysis. We undertook stratified analyses and assessed admission rates over seven months during which lockdown restrictions were gradually lifted.FindingsOur combined dataset included 32 million people who contributed over 74 million person-years. Admission rates for all three conditions fell by 34.2% (Confidence Interval (CI): -43.0, -25.3) in England, 20.9% (CI: -27.8, -14.1) in Scotland, and 24.7% (CI: -36.7, -12.7) in Wales, with falls across every stratum considered. In all three nations, cancer-related admissions fell the most while respiratory-related admissions fell the least (e.g., rates fell by 40.5% (CI: -47.4, -33.6), 21.9% (CI: -35.4, -8.4), and 19.0% (CI: -30.6, -7.4) in England for cancer, cardiovascular-related, and respiratory-related admissions respectively). Unscheduled admissions rates fell more in the most than the least deprived quintile across all three nations. Some ethnic minority groups experienced greater falls in admissions (e.g., in England, unscheduled admissions fell by 9.5% (CI: -20.2, 1.2) for Whites, but 44.3% (CI: -71.0, -17.6), 34.6% (CI: -63.8, -5.3), and 25.6% (CI: -45.0, -6.3) for Mixed, Other and Black ethnic groups respectively). Despite easing of restrictions, the overall admission rates remained lower in England, Scotland, and Wales by 20.8%, 21.6%, and 22.0%, respectively when compared to the same period (August-September) during the pre-pandemic years. This corresponds to a reduction of 26.2, 23.8 and 30.2 admissions per 100,000 people in England, Scotland, and Wales respectively.InterpretationHospital care for non-COVID diseases fell substantially across England, Scotland, and Wales during the first lockdown, with reductions persisting for at least six months. The most deprived and minority ethnic groups were impacted more severely.FundingThis work was funded by the Medical Research Council as part of the Lifelong Health and Wellbeing study as part of National Core Studies (MC_PC_20030). SVK acknowledges funding from the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE - The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. BG has received research funding from the NHS National Institute for Health Research (NIHR), the Wellcome Trust, Health Data Research UK, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme.
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Project description:Preliminary evidence from China and other countries has suggested that coronavirus disease 2019 (COVID-19) mitigation measures have caused a decline in preterm births, but evidence is conflicting. Utilising a national representative data of 11,714,947 pregnant women in China, we explored the immediate changes in preterm birth rates during the COVID-19 mitigation period using an interrupted-time-series analysis. We defined the period prior to February 1, 2020 as the baseline, followed by the COVID-19 mitigation stage. In the first month of the COVID-19 mitigation, a significant absolute decrease in preterm birth rates of 0.68% (95%CI:-1.10% to -0.26%) in singleton, and of 2.80% (95%CI:-4.51% to -1.09%) in multiple births was noted. This immediate decline in Wuhan was greater than that at the national level among singleton births [-2.21% (95%CI:-4.09% to -0.34% vs. -0.68%)]. Here we report an immediate impact of COVID-19 mitigation measures on preterm birth in China.
| S-EPMC9440464 | biostudies-literature
Project description:Following the introduction of unprecedented "stay-at-home" national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities.
| S-EPMC7288252 | biostudies-literature
Project description:BackgroundInterrupted time series (ITS) analysis is a time series regression model that aims to evaluate the effect of an intervention on an outcome of interest. ITS analysis is a quasi-experimental study design instrumental in situations where natural experiments occur, gaining popularity, particularly due to the Covid-19 pandemic. However, challenges, including the lack of a control group, have impeded the quantification of the effect size in ITS. The current paper proposes a method and develops a user-friendly R package to quantify the effect size of an ITS regression model for continuous and count outcomes, with or without seasonal adjustment.ResultsThe effect size presented in this work, together with its corresponding 95% confidence interval (CI) and P-value, is based on the ITS model-based fitted values and the predicted counterfactual (the exposed period had the intervention not occurred) values. A user-friendly R package to fit an ITS and estimate the effect size was developed and accompanies this paper. To illustrate, we implemented a nation population-based ITS study from January 2001 to May 2021 covering the all-cause mortality of Israel (n = 9,350 thousand) to quantify the effect size of Covid-19 exposure on mortality rates. In the period unexposed to the Covid-19 pandemic, the mortality rate decreased over time and was expected to continue decreasing had Covid-19 not occurred. In contrast, the period exposed to the Covid-19 pandemic was associated with an increased all-cause mortality rate (relative risk = 1.11, 95% CI = 1.04, 1.18, P < 0.001).ConclusionFor the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure.
| S-EPMC9652048 | biostudies-literature
Project description:BackgroundChina implemented strict non-pharmaceutical interventions to contain COVID-19 at the early stage. We aimed to evaluate the impact of COVID-19 on HIV care continuum in China.MethodsAggregated data on HIV care continuum between 1 January 2017 and 31 December 2020 were collected from centers for disease control and prevention at different levels and major infectious disease hospitals in various regions in China. We used interrupted time series analysis to characterize temporal trend in weekly numbers of HIV post-exposure prophylaxis (PEP) prescriptions, HIV tests, HIV diagnoses, median time intervals between HIV diagnosis and antiretroviral therapy (ART) initiation (time intervals, days), ART initiations, mean CD4+ T cell counts at ART initiation (CD4 counts, cells/μL), ART collections, and missed visits for ART collection, before and after the implementation of massive NPIs (23 January to 7 April 2020). We used Poisson segmented regression models to estimate the immediate and long-term impact of NPIs on these outcomes.FindingsA total of 16,780 PEP prescriptions, 1,101,686 HIV tests, 69,659 HIV diagnoses, 63,409 time intervals and ART initiations, 61,518 CD4 counts, 1,528,802 ART collections, and 6656 missed visits were recorded during the study period. The majority of outcomes occurred in males (55·3-87·4%), 21-50 year olds (51·7-90·5%), Southwestern China (38·2-82·0%) and heterosexual transmission (47·9-66·1%). NPIs was associated with 71·5% decrease in PEP prescriptions (IRR 0·285; 95% CI 0·192-0·423), 36·1% decrease in HIV tests (0·639, 0·497-0·822), 32·0% decrease in HIV diagnoses (0·680, 0·511-0·904), 59·3% increase in time intervals (1·593, 1·270-1·997) and 17·4% decrease in CD4 counts (0·826, 0·746-0·915) in the first week during NPIs. There was no marked change in the number of ART initiations, ART collections and missed visits during the NPIs. By the end of 2020, the number of HIV tests, HIV diagnoses, time intervals, ART initiations, and CD4 counts reached expected levels, but the number of PEP prescriptions (0·523, 0·394-0·696), ART collections (0·720, 0·595-0·872), and missed visits (0·137, 0·086-0·220) were still below expected levels. With the ease of restrictions, PEP prescriptions (slope change 1·024/week, 1·012-1·037), HIV tests (1·016/week, 1·008-1·026), and CD4 counts (1·005/week, 1·001-1·009) showed a significant increasing trend.InterpretationHIV care continuum in China was affected by the COVID-19 NPIs at various levels. Preparedness and efforts to maintain the HIV care continuum during public health emergencies should leverage collaborations between stakeholders.FundingNatural Science Foundation of China.
| S-EPMC9365399 | biostudies-literature
Project description:ObjectiveTo investigate the possible impact of lockdown policies on the diagnosis and treatment of cancer patients in Henan, China.Design setting and participantsWe collected data from the Henan Cancer Hospital, affiliated with Zhengzhou University. The monthly numbers of inpatient admissions from January 2014 to December 2019 were used to forecast the number of inpatient admissions in 2020, which was then compared to the actual number of patients admitted during the pandemic to evaluate how the actual number diverges from this forecast. We conducted an interrupted time series analysis using the autoregressive integrated moving average (ARIMA) model.Main outcomes and measuresFor specific diagnoses, treatment modalities, and age groups, we compared the changes in monthly admissions after the pandemic with the forecasted changes from the model.ResultsThe observed overall monthly number of inpatient admissions decreased by 20.2% [95% confidence interval (CI), 11.7-27.2%], 78.9% (95% CI, 77.3-80.4%), and 40.9% (95% CI, 35.6-45.5%) in January, February, and March 2020, respectively, as compared with those predicted using the ARIMA model. After the lockdown, visits for all treatment modalities decreased sharply. However, apparent compensation and recovery of the backlog appeared in later surgeries. As a result, the number of patients who underwent surgery in 2020 (30,478) was close to the number forecasted by the ARIMA model (30,185). In the same period, patients who received other treatments or underwent examinations were 106,074 and 36,968, respectively; the respective numbers that were forecasted by ARIMA were 127,775 and 60,025, respectively. These findings depict a decrease of 16.9 and 38.4% in patients who received other treatments or underwent examinations only, respectively. Regarding diagnosis, the reported incidence of various cancers decreased dramatically in February, with varying extent and speed of recovery.Conclusion and relevanceThe COVID-19 pandemic has significantly delayed the diagnosis and treatment of cancer in Henan, China. Long-term research should be conducted to assess the future effects of lockdown policies.
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