Monthly Incidence Rate Research Articles

No evidence for seasonal variations of the incidence of testicular germ cell tumours in Germany.

The pathogenesis of testicular germ cell tumours (GCTs) is still incompletely understood. Any progress in its understanding must derive from observational studies. Recently, it has been suggested that the incidence of GCTs may follow a seasonal pattern based on circannual changes in the Vitamin D serum levels, with maximum incidence rates in winter months. To examine this promising hypothesis, we studied monthly incidence rates of testicular GCTs in Germany by analysing 30,988 GCT cases aged 15-69 years, diagnosed during 2009-2019. Monthly incident case numbers with data regarding histology and patient age were obtained from the Robert Koch Institut, Berlin, along with annual male population counts. We used precision weighting for deriving pooled monthly incidence rates for GCTs of the period 2009-2019. We stratified pooled rates by histology (seminoma and nonseminoma) and age (15-39 and 40-69 years). By assuming a cyclical effect, we used an estimator of the intensity of seasonal occurrence and report seasonal relative risks (RR). The mean monthly incidence rate was 11.93/105 person-months. The seasonal RR for testicular cancer over-all is 1.022 (95% CI 1.000-1.054). The highest seasonal RR was found in the subgroup of nonseminoma aged 15-39 years, with a RR 1.044 (95% CI 1.000-1.112). The comparison of the pooled monthly rates of the winter months (October-March) with the summer months (April-September) revealed a maximum relative difference of 5% (95% CI 1-10%) for nonseminoma, aged 15-39 years. We conclude that there is no evidence of a seasonal variation of incidence rates of testicular cancer. Our results are at odds with an Austrian study, but the present data appear sound because the results were obtained with precision weighted monthly incidence rates in a large population of GCT cases.

Data-Driven Assessment of Adolescents’ Mental Health During the COVID-19 Pandemic

Adolescents' mental health was severely compromised during the COVID-19 pandemic. Longitudinal real-world studies on changes in mental health of adolescents during the later phase of the pandemic are limited. We aimed to quantify the effect of COVID-19 pandemic on adolescents' mental health outcomes based on electronic health records (EHR). A retrospective cohort study utilizing the computerized database of a 2.5 million members' state-mandated health organization in Israel. Rates of mental health diagnoses, and psychiatric drug dispensations were measured among adolescents aged 12-17 with and without pre-existing mental history, for 2017-2021 years. Relative risks were computed between the years and interrupted time series (ITS) analysis evaluated changes in monthly incidence rates of psychiatric outcomes. Average population size was 218,146 in 2021. During the COVID-19 period a 36% increase was observed in the incidence of depression (95%CI: 25-47), 31% in anxiety (95%CI: 23-39), 20% in stress (95%CI: 13-27), 50% in eating disorders (95%CI: 35-67), 25% in antidepressants (95%CI: 25-33) and 28% in antipsychotics (95%CI: 18-40). A decreased rate of 26% (95% CI: 0.80-0.88) was observed in ADHD diagnoses. The increase of the examined outcomes was most prominent among youth without psychiatric history, females, general secular Jewish population, medium-high SES, and 14-15 years age group. ITS analysis confirmed a significantly higher growth in the incidence of psychiatric outcomes during the COVID-19 period, compared to previous years. This real-world study highlights the deterioration of adolescents' mental health during the COVID-19 pandemic and suggests that youth mental health should be considered during health policy decision making.

SG-APSIC1097: The impact of COVID-19 on the incidence of carbapenem-resistant Enterobacterales (CRE) in Singapore: An interrupted time-series analysis

Objectives: Over the past 2 years, many infection prevention and control (IPC) resources have been diverted to manage the COVID-19 pandemic. Its impact on the incidence of antimicrobial-resistant organisms has not been adequately studied. We investigated the impact of the pandemic on the incidence of carbapenem-resistant Enterobacterales (CRE) in Singapore. Methods: We extracted data on unique CRE isolates (clinical and/or surveillance cultures) and patient days for 6 public hospitals in Singapore from the carbapenemase-producing Enterobacteriaceae (CaPES) study group database, and we calculated the monthly incidence of CRE (per 10,000 patient days). Interrupted time-series (ITS) analysis was conducted with the pre–COVID-19 period defined as before February 2020, and the COVID-19 period defined as after February 2020. Statistical analyses were performed using Stata version 15 software. Results: From January 2017 to March 2021, 6,770 CRE isolates and 9,126,704 patient days were documented. The trend in CRE monthly incidence increased significantly during the pre–COVID-19 period (0.060; 95% CI, 0.033–0.094; P < .001) but decreased during the COVID-19 period (−0.183; 95% CI, −0.390 to 0.023; P = .080) without stepwise change in the incidence (−1.496; 95% CI, −3.477 to 0.485; P = .135). The trend in monthly incidence rate of CRE clinical cultures increased significantly during the pre–COVID-19 period (0.046; 95% CI, 0.028–0.064; P < .001) and decreased significantly during COVID-19 period (−0.148; 95% CI, −0.249 to −0.048; P = .048) with no stepwise change in the incidence (−0.063; 95% CI, −0.803 to 0.677; P = .864). The trend in monthly incidence rate of CRE surveillance cultures decreased during the pre–COVID-19 period (−0.020; 95% CI, −0.062 to 0.022; P = .341) and the COVID-19 period (−0.067; 95% CI, −0.291to 0.158; P = .552) without stepwise change in the incidence (−1.327; 95% CI, −3.535 to 0.881; P = .233). Conclusions: The rate of CRE in clinical cultures decreased during COVID-19 but not the rate in surveillance cultures. Further studies are warranted to study the impact of COVID-19 on CREs.(DUPLICATE DELETED)

Retrospective study on bovine clinical mastitis and associated milk loss during the month of its peak occurrence at the National Dairy Farm in the Emirate of Abu Dhabi, United Arab Emirates.

Commercial dairy establishments are relatively young in the United Arab Emirates (UAE), and as a result, there is lack of epidemiological data on mastitis in dairy farms. A retrospective data of seven years (2015-2021) were used to estimate the cumulative average monthly incidence rate of bovine clinical mastitis and evaluate associated milk loss at the National Dairy Farm. Data were extracted from the records of lactating dairy cows (n = 1300-1450) and analyzed using repeated measure and one-way ANOVA, non-parametric Spearman correlation, paired and unpaired t tests. The highest average cumulative monthly incidence rate was 49 cases per 1000 cows-year that was recorded in 2019 while the lowest was 19 cases per 1000 cows-year in 2021. The cumulative average monthly incidence rate of clinical mastitis significantly (p < 0.001) varied among the seven years. The cumulative average monthly incidence rate was associated with average monthly humidity (p < 0.01) and average monthly rainfall (p < 0.05); however, it was not associated with the average monthly temperature (p > 0.05). The average daily milk yield of cows with clinical mastitis (Mean ± SEM; 18.6 ± 0.54 kg) was significantly (p < 0.001) lower than the average daily milk yield of clinical mastitis free cows (40.5 ± 0.29 kg). The largest average monthly milk loss due to clinical mastitis was 5% of the average total monthly milk production in 2019 while the lowest was 2% of the average total monthly milk production in 2021. The result of the study indicated the direct influence of weather conditions such as increased rainfall and humidity, which caused an upsurge in the incidence rate of clinical mastitis, leading to an increased loss in milk and hence the economy of the dairy farm. Proactive preventive measures along with good dairy farm practices that help mitigate the impacts of harsh weather conditions are recommended.

Trends and disparities in 44 national notifiable infectious diseases in China: An analysis of national surveillance data from 2010 to 2019.

Research assessing the changing epidemiology of infectious diseases in China after the implementation of new healthcare reform in 2009 was scarce. We aimed to get the latest trends and disparities of nationalnotifiable infectious diseases by age, sex, province, and season in China from 2010 to 2019. The number of incident cases and deaths, incidence rate, and mortality of 44 national notifiable infectious diseases by sex, age groups, and provincial regions from 2010 to 2019 were extracted from the China Information System for Disease Control and Prevention and official reports and divided into six kinds of infectious diseases by transmission routes and three classes (A-C) in this descriptive study. Estimated annual percentage changes (EAPCs) were calculated to quantify the temporal trends of incidence and mortality rate. We calculated the concentration index to measure economic-related inequality. Segmented interrupted time-series analysis was used to estimate the impact of the COVID-19 pandemic on the epidemic of notifiable infectious diseases. The trend of incidence rate on six kinds of infectious diseases by transmission routes was stable, while only mortality of sexual, blood-borne, and mother-to-child-borne infectious diseases increased from 0.6466 per 100 000 population in 2010 to 1.5499 per 100 000 population in 2019 by 8.76% per year (95% confidence interval [CI]: 6.88-10.68). There was a decreasing trend of incidence rate on Class-A infectious diseases (EAPC = -16.30%; 95%CI: -27.93 to -2.79) and Class-B infectious diseases (EAPC = -1.05%; 95%CI: -1.56 to -0.54), while an increasing trend on Class-C infectious diseases (EAPC = 6.22%; 95%CI: 2.13-10.48). For mortality, there was a decreasing trend on Class-C infectious diseases (EAPC = -14.76%; 95%CI: -23.46 to -5.07), and an increasing trend on Class-B infectious diseases (EAPC = 4.56%; 95%CI: 2.44-6.72). In 2019, the infectious diseases with the highest incidence rate and mortality were respiratory diseases (340.95 per 100 000 population), and sexual, blood-borne, and mother-to-child-borne infectious diseases (1.5459 per 100 000 population), respectively. The greatest increasing trend of incidence rate was observed in seasonal influenza, from 4.83 per 100 000 population in 2010 to 253.36 per 100 000 population in 2019 by 45.16% per year (95%CI: 29.81-62.33), especially among females and children aged 0-4 years old. The top disease with the highest mortality was still AIDs, which had the highest average yearly mortality in 24 provinces from 2010 to 2019, and its incidence rate (EAPC = 14.99%; 95%CI: 8.75-21.59) and mortality (EAPC = 9.65; 95%CI: 7.71-11.63) both increased from 2010 to 2019, especially among people aged 44-59 years old and 60 or older. Male incidence rate and mortality were higher than females each year from 2010 to 2018 on 29 and 10 infectious diseases, respectively. Additionally, sex differences in the incidence and mortality of AIDS were becoming larger. The curve lay above the equality line, with the negative value of the concentration index, which indicated that economic-related health disparities exist in the distribution of incidence rate and mortality of respiratory diseases (incidence rate: the concentration index = -0.063, p < 0.0001; mortality: the concentration index = -0.131, p < 0.001), sexual, blood-borne, and mother-to-child-borne infectious diseases (incidence rate: the concentration index = -0.039, p = 0.0192; mortality: the concentration index = -0.207, p < 0.0001), and the inequality disadvantageous to the poor (pro-rich). Respiratory diseases (Dec-Jan), intestinal diseases (May-Jul), zoonotic infectious diseases (Mar-Jul), and vector-borne infectious diseases (Sep-Oct) had distinct seasonal epidemic patterns. In addition, segmented interrupted time-series analyses showed that, after adjusting for potential seasonality, autocorrelation, GDP per capita, number of primary medical institutions, and other factors, there was no significant impact of COVID-19 epidemic on the monthly incidence rate of six kinds of infectious diseases by transmission routes from 2018 to 2020 (all p > 0.05). The incidence rates of six kinds of infectious diseases were stable in the past decade, and incidence rates of Class-A and Class-B infectious diseases were decreasingbecause of comprehensive prevention and control measures and a strengthened health system after the implementation of the new healthcare reform in China since2009. However, age, gender, regional, and economic disparities were still observed. Concerted efforts are needed to reduce the impact of seasonal influenza (especially among children aged 0-4 years old) and the mortality of AIDs (especially among people aged 44-59 years old and 60 or older). More attention should be paid to the disparities in the burden of infectious diseases.

Economic Burden and Treatment Patterns Among Patients with Mantle Cell Lymphoma in the US: A Retrospective Claims Analysis

Introduction: Mantle cell lymphoma (MCL) is a rare, aggressive form of non-Hodgkin's lymphoma with relatively poor prognosis compared to other B-cell malignancies, high economic burden, and a changing treatment landscape with recent therapeutic advances. This study describes current treatment patterns, healthcare resource use (HRU), and costs in patients with MCL in the US. Methods: Adult patients with ≥2 diagnosis codes for MCL on ≥2 distinct dates within 12 months were identified in Optum Clinformatics claims data from 10/1/2015 to 3/31/2021. The first observed MCL diagnosis was considered the index date. The baseline period was defined as the 12 months of continuous enrollment pre-index; continuous enrollment was also required for ≥1 month post-index. Patients with diagnosis codes for MCL or other malignancies during baseline were excluded. The study period spanned from the index date till the earliest of either end of continuous enrollment or end of data availability. Demographic and clinical characteristics were described during the baseline period. All-cause and MCL-related HRU in terms of monthly incidence rates and 95% confidence intervals (CI) and per patient per month (PPPM) costs were described during the study period. A subset of patients meeting the following additional criteria were included in the treatment sequence analysis: no claims for treatments of interest during the baseline period and ≥1 claim for treatments during the study period. Treatments of interest included National Comprehensive Cancer Network (NCCN)-recommended systemic therapies, stem cell transplantation (SCT), and chimeric antigen receptor (CAR)-T therapy. An algorithm was developed to identify treatments in first line (1L), second line (2L), and third line (3L) during the study period. HRU and costs were described during the 1L, 2L, and third and subsequent line (3L+) periods. Results: The study included 696 patients with MCL, with a mean follow-up time of 22 months. Patients had a mean age of 71 years and were predominantly male (68%), with most having Medicare coverage (76%). The most common comorbidities during baseline were cardiovascular disease (29%), diabetes (27%), and chronic obstructive pulmonary disease (24%), with a mean National Cancer Institute Comorbidity Index (NCICI) of 1.9. During the study period, there were 0.13 (95% confidence interval: 0.12, 0.14) all-cause hospitalizations, 3.27 outpatient visits (3.24, 3.30), 0.06 (0.06, 0.07) emergency room (ER) visits, and 0.18 (0.18, 0.19) other visits PPPM (Table 1). Majority of hospitalizations were MCL-related (0.09 PPPM). MCL-related outpatient visits (1.57 PPPM), ER visits (0.01 PPPM), and other visits (0.06 PPPM) formed a lower proportion of all-cause visits. Patients had considerable total all-cause costs ($23,884 PPPM), almost all of which were medical costs ($22,717 PPPM). MCL-related medical costs contributed substantially to all-cause costs ($19,771 PPPM), largely due to MCL-related hospitalizations ($12,785 PPPM). 399 patients (57%) who received a treatment of interest during the study period were included in the treatment pattern analysis. Among these patients, 129 (32%) were observed to receive a treatment of interest in 2 or more lines. Bendamustine-based therapies were most used in 1L (51%), followed by SCT and rituximab monotherapy (11% each) (Table 2). Ibrutinib-based therapies were the most common in 2L (28%) and 3L (24%). Mean treatment duration decreased with increasing lines of therapy (173 days for 1L, 154 days for 2L, and 139 days for 3L). All-cause and MCL-related HRU and costs tended to increase with increasing lines of therapy (Table 1) - for example, hospitalization costs were twice as high in 3L+ ($24,314 PPPM for all-cause and $22,840 PPPM for MCL-related hospitalizations) than in 1L ($12,366 PPPM for all-cause and $11,162 PPPM for MCL-related hospitalizations). Conclusions: This study describes the contemporary treatment patterns and economic burden for MCL in the US. Results show that a range of treatments are used to manage MCL, with more recently approved therapies such as ibrutinib being used more commonly in later lines. This study also highlights high HRU and cost burden among patients with MCL, which increases with subsequent lines of therapy. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Estimating the infection burden of COVID-19 in Malaysia.

Malaysia has reported 2.75 million cases and 31,485 deaths as of 30 December 2021. Underestimation remains an issue due to the underdiagnosis of mild and asymptomatic cases. We aimed to estimate the burden of COVID-19 cases in Malaysia based on an adjusted case fatality rate (aCFR). Data on reported cases and mortalities were collated from the Ministry of Health official GitHub between 1 March 2020 and 30 December 2021. We estimated the total and age-stratified monthly incidence rates, mortality rates, and aCFR. Estimated new infections were inferred from the age-stratified aCFR. The total estimated infections between 1 March 2020 and 30 December 2021 was 9,955,000-cases (95% CI: 6,626,000-18,985,000). The proportion of COVID-19 infections in ages 0-11, 12-17, 18-50, 51-65, and above 65 years were 19.9% (n = 1,982,000), 2.4% (n = 236,000), 66.1% (n = 6,577,000), 9.1% (n = 901,000), 2.6% (n = 256,000), respectively. Approximately 32.8% of the total population in Malaysia was estimated to have been infected with COVID-19 by the end of December 2021. These estimations highlight a more accurate infection burden in Malaysia. It provides the first national-level prevalence estimates in Malaysia that adjusted for underdiagnosis. Naturally acquired community immunity has increased, but approximately 68.1% of the population remains susceptible. Population estimates of the infection burden are critical to determine the need for booster doses and calibration of public health measures.

Trends in non-COVID-19 hospitalizations prior to and during the COVID-19 pandemic period, United States, 2017–2021

COVID-19 pandemic-related shifts in healthcare utilization, in combination with trends in non-COVID-19 disease transmission and non-pharmaceutical intervention use, had clear impacts on rates of hospitalization for infectious and chronic diseases. Using a U.S. national healthcare billing database, we estimated the monthly incidence rate ratio of hospitalizations between March 2020 and June 2021 according to 19 ICD-10 diagnostic chapters and 189 subchapters. The majority of primary diagnoses for hospitalization showed an immediate decline in incidence during March 2020. Hospitalizations for reproductive neoplasms, hypertension, and diabetes returned to pre-pandemic levels during late 2020 and early 2021, while others, like those for infectious respiratory disease, did not return to pre-pandemic levels during this period. Our assessment of subchapter-level primary hospitalization codes offers insight into trends among less frequent causes of hospitalization during the COVID-19 pandemic in the U.S.

Predicting incidence of hepatitis E for thirteen cities in Jiangsu Province, China.

Hepatitis E has placed a heavy burden on China, especially in Jiangsu Province, so accurately predicting the incidence of hepatitis E benefits to alleviate the medical burden. In this paper, we propose a new attentive bidirectional long short-term memory network (denoted as BiLSTM–Attention) to predict the incidence of hepatitis E for all 13 cities in Jiangsu Province, China. Besides, we also explore the performance of adding meteorological factors and the Baidu (the most widely used Chinese search engine) index as additional training data for the prediction of our BiLSTM–Attention model. SARIMAX, GBDT, LSTM, BiLSTM, and BiLSTM–Attention models are tested in this study, based on the monthly incidence rates of hepatitis E, meteorological factors, and the Baidu index collected from 2011 to 2019 for the 13 cities in Jiangsu province, China. From January 2011 to December 2019, a total of 29,339 cases of hepatitis E were detected in all cities in Jiangsu Province, and the average monthly incidence rate for each city is 0.359 per 100,000 persons. Root mean square error (RMSE) and mean absolute error (MAE) are used for model selection and performance evaluation. The BiLSTM–Attention model considering meteorological factors and the Baidu index has the best performance for hepatitis E prediction in all cities, and it gets at least 10% improvement in RMSE and MAE for all 13 cities in Jiangsu province, which means the model has significantly improved the learning ability, generalizability, and prediction accuracy when comparing with others.

The Disproportionate Impact of Coronavirus Disease 2019 (COVID-19) Pandemic on Healthcare-Associated Infections in Community Hospitals: Need for Expanding the Infectious Disease Workforce.

BackgroundThe COVID-19 pandemic had a considerable impact on US healthcare systems, straining hospital resources, staff, and operations. However, a comprehensive assessment of the impact on healthcare associated infections (HAIs) across different hospitals with varying level of infectious disease (ID) physician expertise, resources, and infrastructure is lacking.MethodsThis retrospective longitudinal multi-center cohort study included central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), C. difficile infections (CDIs), and ventilator-associated events (VAEs) from 53 hospitals (academic and community) in Southeastern United States from January 1, 2018 to March 31, 2021. Segmented negative binomial regression generalized estimating equations models estimated changes in monthly incidence rates in the baseline (01/2018 – 02/2020) compared to the pandemic period (03/2020 – 03/2021, further divided into three pandemic phases).ResultsCLABSIs and VAEs increased by 24% and 34% respectively during the pandemic period. VAEs increased in all phases of the pandemic, while CLABSIs increased in later phases of the pandemic. CDI trend increased by 4.2% per month in the pandemic period. On stratifying the analysis by hospital characteristics, the impact of the pandemic on healthcare-associated infections was more significant in smaller sized and community hospitals. CAUTIs did not change significantly during the pandemic across all hospital types.ConclusionsCLABSIs, VAEs, and CDIs increased significantly during the pandemic, especially in smaller community hospitals, most of which lack ID physician expertise. Future efforts should focus on better understanding challenges faced by community hospitals, strengthening infection prevention infrastructure, and expanding the ID workforce, particularly to community hospitals.

Applying SARIMA, ETS, and hybrid models for prediction of tuberculosis incidence rate in Taiwan.

BackgroundTuberculosis (TB) remained one of the world’s most deadly chronic communicable diseases. Future TB incidence prediction is a benefit for intervention options and resource-allocation planning. We aimed to develop rapid univariate prediction models for epidemics forecasting employment.MethodsThe surveillance data regarding Taiwan monthly TB incidence rates which from January 2005 to June 2017 were utilized for simulation modelling and from July 2017 to December 2020 for model validation. The modeling approaches including the Seasonal Autoregressive Integrated Moving Average (SARIMA), the Exponential Smoothing (ETS), and SARIMA-ETS hybrid algorithms were constructed and compared. The modeling performance of in-sample simulating training sets and pseudo-out-of-sample validating sets were evaluated by metrics of the root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), and mean absolute scaled error (MASE).ResultsA total of 191,526 TB cases with a highest incidence rate in 2005 (72.5 per 100,000 person-year) and lowest in 2020 (33.2 per 100,000 person-year), from January-2005 to December-2020 showed a seasonality and steadily declining trend in Taiwan. The monthly incidence rates data were utilized to formulate these forecasting models. Through stepwise screening and assessing of the accuracy metrics, the optimized SARIMA(3,0,0)(2,1,0)12, ETS(A,A,A) and SARIMA-ETS-hybrid models were respectively selected as the candidate models. Regarding the outcome assessment of model performance, the SARIMA-ETS-hybrid model outperformed the ARIMA and ETS in the short term prediction with metrics of RMSE, MAE MAPE, and MASE of 0.084%, 0.067%, 0.646%, and 0.870%, during the pseudo-out-of-sample forecasting period. After projecting ahead to the long term forecasting TB incidence rates, ETS model showed the best performance resulting as a 41.69% (range: 22.1–56.38%) reduction of TB epidemics in 2025 and a 54.48% (range: 33.7–68.7%) reduction in 2030 compared with the 2015 levels.ConclusionThis time series modeling might offer us a rapid surveillance tool for facilitating WHO’s future TB elimination milestone. Our proposed SARIMA-ETS or ETS model outperformed the SARIMA in predicting less or 12–30 months ahead of epidemics, and all models showed better in short or medium-term forecasting than long-term forecasting.

Changes in the Incidence Rates of Gastrointestinal Diseases Due to the COVID-19 Pandemic in South Korea: A Long-Term Perspective.

We investigated whether the coronavirus disease 2019 (COVID-19) pandemic, in conjunction with public health measures, influenced the incidence of gastrointestinal diseases according to age and sex during the pandemic. Changes in the monthly incidence rates (January 2018 to June 2021) of common gastrointestinal diseases were assessed using data from the Korean National Health Insurance Service by comparing the data of two periods: before COVID-19 (January 2018–February 2020) and during COVID-19 (March 2020–June 2021). The Mann–Whitney U test and Levene’s test were used to compare the differences in the incidences before and during the pandemic. In the pandemic period, compared to in the pre-COVID-19 period, the incidence rates of ulcerative colitis, Crohn’s disease, cholelithiasis, and esophageal reflux significantly increased, whereas those of infective enteritis and irritable bowel syndrome decreased, regardless of age or sex. There were no significant changes in the incidence rates of pancreatitis, acute appendicitis, liver cirrhosis, and hemorrhoids. No seasonal variations in gastrointestinal disease occurrence were observed. In conclusion, the COVID-19 pandemic may have had unprecedented and long-term impacts on the epidemiology of gastrointestinal disease. These changes may indicate a substantial future burden on healthcare resources during the recovery phase of the pandemic and thereafter.

Incidence and predictors of priapism events in sickle cell anemia: a diary-based analysis

AbstractWe conducted one of the first prospective studies to test the hypothesis that the clinical history of priapism underestimates priapism incidence compared with a priapism pain diary. Eligibility criteria were men with sickle cell anemia (SCA) between 18 and 40 years of age who have had at least 3 episodes of priapism in the past 12 months. Seventy-one men with SCA completed the diary for at least 3 months. The first 3 months of the priapism diary were included in the analysis. A total of 298 priapism episodes were recorded, and 80% (57 of 71) of the participants had at least 1 priapism event. Priapism severity was reported in the range of moderate to the worst imaginable pain in 81.5% (263 of 298), and a total 57 participants (80%) had a median pain rating of 6 (interquartile range: 5-8) on a scale from 1 to 10. The monthly incidence rate of priapism per participant based on history versus self-report pain diary was 2.0 (95% confidence interval, 1.9-2.1) and 1.4 (95% confidence interval, 1.2-1.6), respectively (P < .001). For participants that had a prior priapism episode, 80% had another episode during the 3-month interval follow-up. The median time to that second episode was 27.5 days. Major priapism occurred in 9.9% of episodes and was associated with the sum of all prospective priapism events. Men with SCA and at least 3 priapism episodes in the past 12 months are at significant risk for recurrent priapism in the following 3 months.

Effect of national COVID-19 lockdown on the incidence of muscle, tendon and ligament injuries and related surgical procedures in the working-aged Finnish population

IntroductionThe effect of lockdown on the incidence of fractures and severe injuries has been widely studied, whereas studies regarding muscle, tendon, and ligament injuries have not received as much attention. The aim of the study was to investigate the effect of the lockdown and later regional regulations due to the COVID pandemic on the incidence of muscle, tendon, and ligament injuries and related surgical procedures.Materials and methodsThis study focuses on the working-age population in the catchment areas of three major Finnish hospitals. Patients were divided into three age groups 18–34, 35–50 and 51–65 years of age. Suitable injuries were retrieved from the data using appropriate ICD-10 codes and procedure codes. The monthly incidence rate ratio (IRR), with 95% confidence intervals (CI), were compared between the year 2020 and the reference years 2017–2019.ResultsUpper and lower extremity injury ED visits decreased by 15.7 and 8.2%. For upper extremity injuries, a decrease in incidence was observed for all three age groups in March (IRR 0.52, CI 0.33–0.80), (IRR 0.53, CI 0.31–0.91), (IRR 0.60, CI 0.38–0.95), respectively. An increase in 18–34 years of age group was detected in June (IRR 1.49, CI 1.05–2.13). Lower extremity injuries decreased in 18–34 years of age group in March (IRR 0.62, CI 0.43–0.90) and April (IRR 0.60, CI 0.42–0.87).A decrease on the incidence of surgeries was observed in April for the 35–50 (IRR 0.53, CI 0.29–0.97) and 51–65 years of age groups (IRR 0.58, CI 0.34–0.98).ConclusionsThe nationwide lockdown in spring 2020 led to a notable decrease in the incidence of emergency department visits and the surgical treatment of muscle, tendon, and ligament injuries in Finland.

Application of the ARIMA Model in Forecasting the Incidence of Tuberculosis in Anhui During COVID-19 Pandemic from 2021 to 2022.

ObjectiveForecasting the seasonality and trend of pulmonary tuberculosis is important for the rational allocation of health resources. In this study, we predict the incidence of pulmonary tuberculosis by establishing the autoregressive integrated moving average (ARIMA) model and providing support for pulmonary tuberculosis prevention and control during COVID-19 pandemic.MethodsRegistered tuberculosis(TB) cases from January 2013 to December 2020 in Anhui province were analysed using traditional descriptive epidemiological methods. Then we used the monthly incidence rate of TB from January 2013 through June 2020 to construct ARIMA model, and used the incidence rate from July 2020 to December 2020 to evaluate the forecasting accuracy. Ljung Box test, Akaike's information criterion(AICc), Bayesian information criterion(BIC) and Realtive error were used to evaluate the model fitting and forecasting effect, Finally, the optimal model was used to forecast the expected monthly incidence of tuberculosis for 2021 and 2022 to learn about the incidence trend.ResultsA total of 255,656 TB cases were registered. The reported rate of tuberculosis was highest in 2013 and lowest in 2020. The peak incidence was in March, Tongling (71.97/100,000), Chizhou (59.93/100,000), and Huainan (58.36/100,000) had the highest number of cases. The ratio of male to female incidence was 2.59:1, with the largest proportion of people being between 66 and 75 years old. The main occupation of patients was farmer. ARIMA (0, 1, 1) (0, 1, 1)12 model was the optimal model to forecast the incidence trend of TB.ConclusionTongling, Chizhou, and Huainan should strengthen measures for TB. In particular, the government should pay more attention on elderly people to prevent tuberculosis infections. The rate of TB patient registration and reporting has decreased under the pandemic of COVID-19. The ARIMA model can be a useful tool for predicting future TB cases.

Analysis of Variation in Incidence of Optic Disc Hemorrhage According to Seasonal and Temperature Changes

To investigate seasonal variation in optic disc hemorrhage (DH) by review of fundus photographs representative of 2 calendar years (2019 and 2020). Retrospective, observational trend study. Patients who visited the Glaucoma Clinic of Seoul National University Hospital and underwent fundus photography were included. All available stereo disc photographs and red-free retinal nerve fiber layer photographs taken between January 1, 2019 and December 31, 2020 were retrospectively reviewed. The monthly incidence rate of DH was determined by reference to the photographs. Seasonal temperature information and patients' intraocular pressure (IOP) information were obtained, organized, and analyzed. Fundus images of 13,514 eyes were reviewed, and 454 eyes were confirmed to have DH. Poisson regression analyses revealed that as the temperature (T) increased by 1 °C, the DH risk ratio was reduced to 0.979 (95% confidence interval [CI] 0.969-0.989, P < .01). The DH incidence ratio was 1.53 (95% CI 1.23-1.91, P < .01) for the T <10 °C group relative to the T ≥20 °C group. The IOP of the patients with DH in winter was significantly higher than that measured in summer. DH is affected by temperature, and as such, shows seasonal variability. This variability is believed to be caused by temperature-related factors such as IOP or hematological factors. © 2022 Elsevier Inc. All rights reserved.

Predicting incidence of hepatitis E using machine learning in Jiangsu Province, China.

Hepatitis E is an increasingly serious worldwide public health problem that has attracted extensive attention. It is necessary to accurately predict the incidence of hepatitis E to better plan ahead for future medical care. In this study, we developed a Bi-LSTM model that incorporated meteorological factors to predict the prevalence of hepatitis E. The hepatitis E data used in this study are collected from January 2005 to March 2017 by Jiangsu Provincial Center for Disease Control and Prevention. ARIMA, GBDT, SVM, LSTM and Bi-LSTM models are adopted in this study. The data from January 2009 to September 2014 are used as the training set to fit models, and data from October 2014 to March 2017 are used as the testing set to evaluate the predicting accuracy of different models. Selecting models and evaluating the effectiveness of the models are based on mean absolute per cent error (MAPE), root mean square error (RMSE) and mean absolute error (MAE). A total of 44 923 cases of hepatitis E are detected in Jiangsu Province from January 2005 to March 2017. The average monthly incidence rate is 0.35 per 100 000 persons in Jiangsu Province. Incorporating meteorological factors of temperature, water vapour pressure, and rainfall as a combination into the Bi-LSTM Model achieved the state-of-the-art performance in predicting the monthly incidence of hepatitis E, in which RMSE is 0.044, MAPE is 11.88%, and MAE is 0.0377. The Bi-LSTM model with the meteorological factors of temperature, water vapour pressure, and rainfall can fully extract the linear and non-linear information in the hepatitis E incidence data, and has significantly improved the interpretability, learning ability, generalisability and prediction accuracy.

Incidence of childhood cancer in Canada during the COVID-19 pandemic.

Background:The COVID-19 pandemic has had a major impact on access to health care resources. Our objective was to estimate the impact of the COVID-19 pandemic on the incidence of childhood cancer in Canada. We also aimed to compare the proportion of patients who enrolled in clinical trials at diagnosis, presented with metastatic disease or had an early death during the first 9 months of the COVID-19 pandemic compared with previous years.Methods:We conducted an observational study that included children younger than 15 years with a new diagnosis of cancer between March 2016 and November 2020 at 1 of 17 Canadian pediatric oncology centres. Our primary outcome was the monthly age-standardized incidence rates (ASIRs) of cancers. We evaluated level and trend changes using interventional autoregressive integrated moving average models. Secondary outcomes were the proportion of patients who were enrolled in a clinical trial, who had metastatic or advanced disease and who died within 30 days. We compared the baseline and pandemic periods using rate ratios (RRs) and 95% confidence intervals (CIs).Results:Age-standardized incidence rates during COVID-19 quarters were 157.7, 164.6, and 148.0 per million, respectively, whereas quarterly baseline ASIRs ranged between 150.3 and 175.1 per million (incidence RR 0.93 [95% CI 0.78 to 1.12] to incidence RR 1.04 [95% CI 0.87 to 1.24]). We found no statistically significant level or slope changes between the projected and observed ASIRs for all new cancers (parameter estimate [β], level 4.98, 95% CI −15.1 to 25.04, p = 0.25), or when stratified by cancer type or by geographic area. Clinical trial enrolment rate was stable or increased during the pandemic compared with baseline (RR 1.22 [95% CI 0.70 to 2.13] to RR 1.71 [95% CI 1.01 to 2.89]). There was no difference in the proportion of patients with metastatic disease (RR 0.84 [95% CI 0.55 to 1.29] to RR 1.22 [0.84 to 1.79]), or who died within 30 days (RR 0.16 [95% CI 0.01 to 3.04] to RR 1.73 [95% CI 0.38 to 15.2]).Interpretation:We did not observe a statistically significant change in the incidence of childhood cancer, or in the proportion of children enrolling in a clinical trial, presenting with metastatic disease or who died early during the first 9 months of the COVID-19 pandemic, which suggests that access to health care in pediatric oncology was not reduced substantially in Canada.

Impact of COVID-19 lockdown on surgical procedures for retinal detachment in France: a national database study

Background/aimsThe COVID-19 crisis and the decisions made regarding population lockdown may have changed patient care. We aimed to investigate the incidence rate of rhegmatogenous retinal detachment (RRD) cases during the...

Calculating clinical mastitis frequency in dairy cows: Incidence risk at cow level, incidence rate at cow level, and incidence rate at quarter level

The lack of standardization in reporting clinical mastitis incidence limits the ability to compare results across multiple studies without additional calculations. There is both a biological and statistical rationale for evaluating the at-risk period at the quarter level. This study aimed to: (1) to outline an applied method for calculating clinical mastitis (CM) incidence rate at the quarter level using currently available software; and (2) to present the results of three different measurements: incidence risk at cow level, incidence rate at cow level, and incidence rate at quarter level. In an open population prospective cohort of eight commercial dairy farms monitored from May 15, 2016, to May 31, 2017, all CM cases (n = 7513) were identified by trained on-farm personnel, who collected all milk samples from all quarters with visibly abnormal milk. Microbiological identification was determined by culture and MALDI-TOF. All lactating quarters were at risk for CM. A quarter was at risk for a new CM case if there was at least 14 d between a previously diagnosed case and the current case in the same quarter, or if a different pathogen was isolated in the same quarter within 14 d. A total of 17,513,429 quarters days at risk (QDAR) were estimated. A statistical software macro and Structured Query Language (SQL) were used to bring all data together. The monthly incidence rate at the cow level was 16.6 cases per 10,000 cow-days, the monthly incidence rate at the quarter level was 4.4 cases per 10,000 QDAR and the monthly incidence risk at the cow level was 4.8 cases per 100 cows. Although the evaluation of QDAR requires additional computation when compared to other methods, it might allow for a more precise evaluation of the data and a more accurate evaluation of mastitis incidence. Clearly defining the methods used to report mastitis incidence will improve our ability to discuss and learn about the differences and similarities across studies, regions, and countries.