Monthly Number Of Cases Research Articles

Prediction of acute onset of chronic cor pulmonale: comparative analysis of Holt-Winters exponential smoothing and ARIMA model

BackgroundThe aim of this study is to analyze the trend of acute onset of chronic cor pulmonale at Chenggong Hospital of Kunming Yan’an Hospital between January 2018 and December 2022.Additionally, the study will compare the application of the ARIMA model and Holt-Winters model in predicting the number of chronic cor pulmonale cases.MethodsThe data on chronic cor pulmonale cases from 2018 to 2022 were collected from the electronic medical records system of Chenggong Hospital of Kunming Yan’an Hospital. The ARIMA and Holt-Winters models were constructed using monthly case numbers from January 2018 to December 2022 as training data. The performance of the model was tested using the monthly number of cases from January 2023 to December 2023 as the test set.ResultsThe number of acute onset of chronic cor pulmonale in Chenggong Hospital of Kunming Yan’an Hospital exhibited a downward trend overall from 2018 to 2022. There were more cases in winter and spring, with peaks observed in November to December and January of the following year. The optimal ARIMA model was determined to be ARIMA (0,1,1) (0,1,1)12, while for the Holt-Winters model, the optimal choice was the Holt-Winters multiplicative model. It was found that the Holt-Winters multiplicative model yielded the lowest error.ConclusionThe Holt-Winters multiplicative model predicts better accuracy. The diagnosis of acute onset of chronic cor pulmonale is related to many risk factors, therefore, when using temporal models to fit and predict the data, we must consider such factors’ influence and try to incorporate them into the models.

IMPLEMENTATION OF VECTOR AUTOREGRESSIVE (VAR) AND VECTOR ERROR CORRECTION MODEL (VECM) METHOD IN PNEUMONIA PATIENTS WITH WEATHER ELEMENTS IN PANGKALPINANG CITY

The news about Covid-19 is no longer as scary as in previous years. As COVID-19 cases decrease, health protocols are becoming more relaxed, making it easier for the virus to spread. Besides COVID-19, ARI is one of Indonesia's leading causes of death for children under five. Around 20-40% of hospital admissions are children due to ARI, with around 1.6 million deaths due to pneumonia alone in children under five per year. Currently, ARI dominates the diseases most suffered by the people of Bangka Belitung. Based on this, using the VAR and VECM method to analyze pneumonia sufferers in toddlers regarding weather elements in the Pangkalpinang City. The VAR model has a simpler structure with a minimal number of variables where all the variables are endogenous, with the independent variable being the lag. Meanwhile, VECM can be used to model cointegrated and non-stationary time series data. The data used in this research is the number of monthly cases of toddlers suffering from pneumonia and data on climate conditions, namely rainfall, air temperature, air humidity and duration of sunlight during 2019-2021 in Pangkalpinang City. The results of the Granger Causality test show that the pneumonia variables regarding rainfall, temperature, duration of sunlight and humidity only have a one-way causality pattern. The VAR estimation results show that weather elements (rainfall, temperature and duration of sunlight) do not significantly affect pneumonia in the short term. Meanwhile, the VECM estimation results show that in the long-term pattern, humidity variables affect pneumonia. For this reason, it is recommended that the relevant agencies carry out outreach to the public, especially to pneumonia sufferers, to avoid damp weather. Because the lower the humidity value, the greater the potential for pneumonia in Pangkalpinang City, Bangka Belitung Islands Province.

Application of advanced very high-resolution radiometer (AVHRR)-based vegetation health indices for modelling and predicting malaria in Northern Benin, West Africa

BackgroundVegetation health (VH) is a powerful characteristic for forecasting malaria incidence in regions where the disease is prevalent. This study aims to determine how vegetation health affects the prevalence of malaria and create seasonal weather forecasts using NOAA/AVHRR environmental satellite data that can be substituted for malaria epidemic forecasts.MethodsWeekly advanced very high-resolution radiometer (AVHRR) data were retrieved from the NOAA satellite website from 2009 to 2021. The monthly number of malaria cases was collected from the Ministry of Health of Benin from 2009 to 2021 and matched with AVHRR data. Pearson correlation was calculated to investigate the impact of vegetation health on malaria transmission. Ordinary least squares (OLS), support vector machine (SVM) and principal component regression (PCR) were applied to forecast the monthly number of cases of malaria in Northern Benin. A random sample of proposed models was used to assess accuracy and bias.ResultsEstimates place the annual percentage rise in malaria cases at 9.07% over 2009–2021 period. Moisture (VCI) for weeks 19–21 predicts 75% of the number of malaria cases in the month of the start of high mosquito activities. Soil temperature (TCI) and vegetation health index (VHI) predicted one month earlier than the start of mosquito activities through transmission, 78% of monthly malaria incidence.ConclusionsSVM model D is more effective than OLS model A in the prediction of malaria incidence in Northern Benin. These models are a very useful tool for stakeholders looking to lessen the impact of malaria in Benin.

Spatial-temporal analysis of hepatitis E in Hainan Province, China (2013-2022): insights from four major hospitals.

Exploring the Incidence, Epidemic Trends, and Spatial Distribution Characteristics of Sporadic Hepatitis E in Hainan Province from 2013 to 2022 through four major tertiary hospitals in the Province. We collected data on confirmed cases of hepatitis E in Hainan residents admitted to the four major tertiary hospitals in Haikou City from January 2013 to December 2022. We used SPSS software to analyze the correlation between incidence rate and economy, population density and geographical location, and origin software to draw a scatter chart and SAS 9.4 software to conduct a descriptive analysis of the time trend. The distribution was analyzed using ArcMap 10.8 software (spatial autocorrelation analysis, hotspot identification, concentration, and dispersion trend analysis). SAS software was used to build an autoregressive integrated moving average model (ARIMA) to predict the monthly number of cases in 2023 and 2024. From 2013 to 2022, 1,922 patients with sporadic hepatitis E were treated in the four hospitals of Hainan Province. The highest proportion of patients (n = 555, 28.88%) were aged 50-59 years. The annual incidence of hepatitis E increased from 2013 to 2019, with a slight decrease in 2020 and 2021 and an increase in 2022. The highest number of cases was reported in Haikou, followed by Dongfang and Danzhou. We found that there was a correlation between the economy, population density, latitude, and the number of cases, with the correlation coefficient |r| value fluctuating between 0.403 and 0.421, indicating a linear correlation. At the same time, a scatter plot shows the correlation between population density and incidence from 2013 to 2022, with r2 values fluctuating between 0.5405 and 0.7116, indicating a linear correlation. Global Moran's I, calculated through spatial autocorrelation analysis, showed that each year from 2013 to 2022 all had a Moran's I value >0, indicating positive spatial autocorrelation (p < 0.01). Local Moran's I analysis revealed that from 2013 to 2022, local hotspots were mainly concentrated in the northern part of Hainan Province, with Haikou, Wenchang, Ding'an, and Chengmai being frequent hotspot regions, whereas Baoting, Qiongzhong, and Ledong were frequent cold-spot regions. Concentration and dispersion analysis indicated a clear directional pattern in the average density distribution, moving from northeast to southwest. Time-series forecast modeling showed that the forecast number of newly reported cases per month remained relatively stable in 2023 and 2024, fluctuating between 17 and 19. The overall incidence of hepatitis E in Hainan Province remains relatively stable. The incidence of hepatitis E in Hainan Province increased from 2013 to 2019, with a higher clustering of cases in the northeast region and a gradual spread toward the southwest over time. The ARIMA model predicted a relatively stable number of new cases each month in 2023 and 2024.

Gender-based violence care in Mauritania: Experience and caseload of six specialized hospital units (2018-2023).

Since 2017, six specialized care units, the USPEC (Unités Spéciales de Prise en Charge) have been implemented in Mauritanian hospitals with the support of the international organization Médicos del Mundo. They provide healthcare and comprehensive assistance to victims of gender-based violence (GBV), such as sexual violence (SV), intimate-partner violence (IPV), female genital mutilation (FGM), adolescent pregnancy and child marriage. In this retrospective, observational study, we investigated the caseload of the six USPEC countrywide between January 1st, 2018, and June 30th, 2023. We analyzed consultation data, victims' sociodemographic characteristics, types of violence they were subjected to, specific patterns-location, relationship with the perpetrator, reoccurrence-, and medical care they received. 3550 cases were attended to, with a threefold increase in the mean number of monthly cases between 2018 and 2023. Women and girls accounted for 95.1% of victims; 78.7% were under 18 years old and 21.9% were under 12. All male victims (n = 172) were children. SV represented 79.8% of the caseload, early marriage/pregnancy 10.4%, IPV 7%, and FGM 0.7%. 80% of perpetrators were known to the victims, and the acts of violence had taken place in the victims´ own home for 60%. The proportion of cases received within 72 hours increased noticeably within the first two years before stabilizing at an average 81.3%. 7.21% of patients received local or surgical treatment and 1.8% were hospitalized. After SV, 996 received emergency contraception while 627, who sought care with delay, were already pregnant. Our findings suggest that the USPEC model responds to both victims' and the health system's needs to address GBV. Prevention, declaration and follow-up of pregnancy as a result of SV in young girls, likely constituted a major motivation for healthcare-seeking, yet more research is needed to document bottlenecks faced by GBV victims to access such services.

РЕАНАЛИЗ ДЕРЕКТЕРІ БОЙЫНША ИНВЕРСИЯ ҚАБАТЫН ТАЛДАУ МҮМКІНДІКТЕРІ

The study of thermal inversion layers in the atmosphere plays an important role in understanding various atmospheric processes and solving environmental and meteorological problems. This work is devoted to evaluating the potential of thermal inversion layer analysis using ERA5 reanalysis data in the nearground layer as an alternative to the limited availability of aerological stations.The characteristics of inversions calculated using ERA5 reanalysis data and radiosonde data from the Karaganda Aerological Station for the period from 2012 to 2021 were compared. General inversions occur most often in January (15...18 times), while in spring and autumn, the average monthly number of cases is 4...10. In the summertime, surface inversions occur most frequently, with a mean monthly value of up to 25 times. The intensity of different surface inversions varies between -1 °C ... -9 °С. The results of the study showed a close similarity between the ERA5 reanalysis data and the radiosonde data. This indicates the suitability of the reanalysis data for studying thermal inversions. This study contributes to the development of knowledge in atmospheric pollution, weather forecasting, aviation meteorology, and the development of climate models by using reanalysis data to study inversion phenomena.

The spatio-temporal distribution of acute encephalitis syndrome and its association with climate and landcover in Vietnam

BackgroundAcute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology.MethodsThe number of monthly cases per province for AES, meningitis and diseases including dengue fever; influenza-like-illness (ILI); hand, foot, and mouth disease (HFMD); and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998–2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed.ResultsThe national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection; temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included.ConclusionsThe positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination campaigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi.

Observation‐driven exponential smoothing

This article presents an approach to forecasting count time series with a form of exponential smoothing built from observation‐driven models. The proposed method is easy to implement and simple to interpret. A variant of the approach is also proposed to handle the impact of outliers on the forecast. The performance of the methodology is studied with simulations and illustrated with an analysis of the number of monthly cases of dengue fever observed in Italy for the years 2008–2021. An R package is made available to enable the reader to reproduce the results discussed in the article.

Cannabidiol exposures in the United States, National Poison Data System, July 2014–June 2021

Introduction There has been an increase in the interest and availability of products asserting to contain cannabidiol (CBD). Objective To describe demographic and clinical patterns in cases involving CBD exposures documented by the America’s Poison Centers (AAPCC). Methods We extracted human exposure cases involving CBD from the U.S. National Poison Data System between July 2014 and June 2021. We described monthly case counts and data on demographics, exposure reason, clinical effects, medical outcomes, and co-exposures, overall and by U.S. Food and Drug Administration (FDA) approval status. Results We identified 6,496 cases, of these, 85.2% involved exposures to non-FDA approved CBD. The monthly number of cases peaked at 336 in March 2021. Cases often occurred in children ages 2–12 years (36.2%). Although in this age group unintentional exposures represented most cases (94.1%), we identified therapeutic errors (3.9%), intentional use (3.0%), and adverse reactions (1.6%) in cases involving exposures to non-FDA approved CBD. Among the 5,248 (80.8%) cases involving exposure to a single product, we identified 44 major medical outcomes, all related to exposures to non-FDA approved CBD. The most frequent clinical effects included neurological, cardiac, and gastrointestinal effects. Among the 1,248 (19.2%) involving exposure to more than one product, the most frequent co-exposures included stimulants and street drugs, sedatives-hypnotics, antipsychotics, and analgesics. Conclusions This case series identified an increasing trend in CBD exposure cases managed by AAPCC. It showed serious medical outcomes in temporal association with exposure to non-FDA approved CBD products. Our findings also suggest both unintentional and intentional use of non-FDA approved CBD in children. Consumers should keep these products out of reach of children and exercise caution when purchasing and using non-FDA approved CBD products.

Trend of hand, foot, and mouth disease from 2010 to 2021 and estimation of the reduction in enterovirus 71 infection after vaccine use in Zhejiang Province, China.

BackgroundZhejiang, ranked in the top three in HFMD (hand, foot, and mouth disease) incidence, is located in the Yangtze River Delta region of southeast China. Since 2016, the EV71 vaccine has been promoted in Zhejiang Province. This study aimed to investigate the trend and seasonal variation characteristics of HFMD from 2010 to 2021 and estimate the reduction in enterovirus 71 infection after vaccine use.MethodsThe data on HFMD cases in Zhejiang Province from January 2010 to December 2021 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and temporal distributions, was computed by the system. The Joinpoint regression model was used to describe continuous changes in the incidence trend. The BSTS (Bayesian structural time-series models) model was used to estimate the monthly number of cases from 2017 to 2021 based on the observed monthly incidence during 2010–2016 by accounting for seasonality and long-term trends. The seasonal variation characteristics of HFMD pathogens were detected by wavelet analysis.ResultsFrom 2010 to 2021, the annual incidence rate fluctuated between 98.81 cases per 100,000 in 2020 and 435.63 cases per 100,000 in 2018, and 1711 severe HFMD cases and 106 fatal cases were reported in Zhejiang Province, China. The annual percent change (APC) in EV71 cases was -30.72% (95% CI: -45.10 to -12.50) from 2016 to 2021. The wavelet transform of total incidence and number of cases of the three pathogens all showed significant periodicity on the 1-year scale. The average 2-year scale periodicity was significant for the total incidence, EV71 cases and Cox A16 cases, but the other enterovirus cases showed significant periodicity on the 30-month scale. The 6-month scale periodicity was significant for the total incidence, EV71 case and Cox A16 case but not for the other enteroviruses case. The relative error percentage of the performance of the BSTS model was 0.3%. The estimated number of cases from 2017 to 2021 after the EV-A71 vaccines were used was 9422, and the reduction in the number of cases infected with the EV71 virus was 73.43% compared to 70.80% when the impact of the COVID-19 epidemic in 2020 was excluded.ConclusionsSince 2010, the incidence of EV71 infections has shown an obvious downward trend. All types of viruses showed significant periodicity on the 1-year scale. The periodicity of the biennial peak is mainly related to EV71 and Cox A16 before 2017 and other enteroviruses since 2018. The half-year peak cycle of HFMD was mainly caused by EV71 and Cox A6 infection. The expected incidence will be 2.76 times(include the cases of 2020) and 2.43 times(exclude the cases of 2020) higher than the actual value assuming that the measures of vaccination are not taken. EV71 vaccines are very effective and should be administered in the age window between 5 months and 5 years.

Comparison of SARIMA model and Holt-Winters model in predicting the incidence of Sjögren's syndrome.

To analyze the prevalence trend of Sjögren's syndrome in the Department of Immunology and Rheumatology of Nanjing Zhongda Hospital from January 2015 to December 2019, and compare the application of SARIMA model and Holt-Winters model in predicting the number of cases of Sjögren's syndrome. All of the data from the Department of Immunology and Rheumatology of Nanjing Zhongda Hospital were collected. The number of monthly cases from January 2015 to December 2019 was regarded as the training set, and it was used to establish the SARIMA model and Holt-Winters model. The number of monthly incidences from January 2020 to December 2020 was regarded as the test set, and it was used to check the model performance. The optimal model of SARIMA is ARIMA (0,1,1) (2,1,1)12 model, and the optimal model of Holt-Winters model is Holt-Winters addition model. It was found that the Holt-Winters addition model produced the smallest error. Holt-Winters addition model produces better prediction accuracy of the model.

Benchmarking Surgeons' Gender and Year of Medical School Graduation Associated With Monthly Operative Workdays for Multispecialty Groups.

BackgroundFemale surgeons reportedly receive less surgical block time and fewer procedural referrals than male surgeons. In this study, we compared operative days between female and male surgeons throughout Florida. Our objective was to facilitate benchmarking by multispecialty groups, both the endpoint to use for statistically reliable results and expected differences.MethodologyThe historical cohort study included all 4,060,070 ambulatory procedural encounters and inpatient elective surgical states performed between January 2017 and December 2019 by 8,472 surgeons at 609 facilities. Surgeons’ gender, year of medical school graduation, and surgical specialty were obtained from their National Provider Identifiers.ResultsFemale surgeons operated an average of 1.0 fewer days per month than matched male surgeons (99% confidence interval 0.8 to 1.2 fewer days, P < 0.0001). The mean differences were 0.8 to 1.4 fewer days per month among each of the five quintiles of years of graduation from medical school (all P ≤ 0.0050). Results were comparable when repeated using the number of monthly cases the surgeons performed.ConclusionsAn average difference of ≤1.4 days per month is a conservative estimate for the current status quo of the workload difference in Florida. Suppose that a group’s female surgeons average more than two fewer operative days per month than the group’s male surgeons of the same specialty. Such a large average difference would call for investigation of what might reflect systematic bias. While such a difference may reflect good flexibility of the organization, it may show a lack of responsiveness (e.g., fewer referrals of procedural patients to female surgeons or bias when apportioning allocated operating room time).

Temporary weather changes and there effect on children respiratory diseases in Ramadi in the year 2017-2018

Temporary weather changes and ther effect on children respiratory diseases in Ramadi in the year 2017-2018The study aims to show how respiratory diseases spread and its connation with seasanol weather changes, thtrough using the number of monthly cases of five diseases depending on the following results: 1. Each (1000) persons have (4.5) cases of Mups . the disease is active during spring, March and April . 2. Each (10000) persons have (0.03) cases of pertussis the disease is active during Spring and Summer ending in May and June . 3. Eavh (1000) persons have (0.04) cases of Poliomyelitis . the disease is active in Summer .4. Each (10000) persons have (1.7) cases of Chicken – pox . the disease is active Spring .5. . Eavh (1000) persons have (0.4) cases of Measles the disease is active in Spring / April and May

Time series analysis of animal bite cases attending anti-rabies clinic.

Rabies is a disease transmitted mostly through animal bites in humans, and seasonal variation in animal bites has been reported by different studies. There has been no study in India using time series analysis for studying monthly variation in animal bite cases. (a) To find out long-term trends and monthly variations in new animal bite cases. (b) To make projections for new animal bite cases. (c) To find out the difference between actual and projected new animal bite cases following the COVID-19 pandemic. A retrolective, record-based study was conducted in a tertiary care facility, Jaipur, and data of new Category II and Category III animal bite cases were taken from January 2007 to December 2021. A multiplicative model was used for conducting time series analysis. The projected monthly number of cases was estimated using the line of best fit based on the least square method. An increasing trend in the annual number of animal bite cases was observed from 7,982 in 2007 to 10,134 in 2019. The monthly index was lowest for the months July to November (0.88 to 0.95), peaked in January (1.14), remained higher from January to June, and fell in July (0.95). The monthly number of new animal bite cases from April 2020 to December 2021 was significantly lower than the projected number (P-value < 0.001). Because the monthly index of animal bite cases was high from January onward, information education and communication (IEC) activities should be increased in the preceding months (November onward) for making people aware of immediate care to be provided to animal bite cases and seek prompt medical care.

Use of Interrupted Time Series Analysis in Understanding the Course of the Congenital Syphilis Epidemic in Brazil

To fight against the rising incidence of syphilis, the Brazilian Ministry of Health (MoH) launched the "Syphilis No!" Project (SNP), with specific resources funded by a parliamentary amendment. Then, in 2018, a national rapid response started to be implemented on the Brazilian Unified Health System (SUS, Sistema Único de Saúde) in two strategic lines (1) to reinforce SUS's universal actions and (2) to implement specific ones to 100 municipalities chosen by the MoH as priorities for syphilis congenital response. In 2015, such localities represented 6895% of congenital syphilis cases in Brazil. In this context, SNP has implemented actions to strengthen epidemiological surveillance of acquired syphilis and congenital syphilis by instituting an integrated and collaborative response through health services networks and reinforcing interstate relations. A quasi-experimental study using time series analysis was conducted to assess immediate impacts and changes to the trend in national congenital syphilis before and after the project, from September 2016 to December 2019. Data were assessed considering rates of congenital syphilis per 1,000 live births in all priority municipalities (n=100) covered by the project and in non-priority municipalities (n=5,470) from all five macro-regions of Brazil. Priority municipalities showed a greater reduction (change in trend) in comparison to non-priority. The linear regression model revealed trend changes after the intervention, with both groups of municipalities showing a drop in the average monthly number of cases per 1,000 live births, with a reduction of -0·21 (CI 95% -0·33 to -0·09; p=0·0011) in priority municipalities and of -0·10 (CI 95% -0.19 to -0.02; p=0·0216) in non-priority municipalities. The study using ITS provides important evidence on the direction, timing, and magnitude of the effects of interventions introduced as part of the SNP on congenital syphilis in Brazil. Our results suggest that the Syphilis No! Project influenced the trends of congenital syphilis in Brazil from 2018, with higher reductions achieved in the priority municipalities. The research is funded by a grant to the Syphilis No! Project from Brazilian Ministry of Health (Project Number: 54/2017). The funders had no role in study design, analysis, decision to publish, or preparation of the manuscript.

Impact of Coronavirus Disease 2019 on the Diagnosis and Therapy for Barrett’s Esophagus and Esophageal Cancer in the United States

Impact of Coronavirus Disease 2019 on the Diagnosis and Therapy for Barrett’s Esophagus and Esophageal Cancer in the United States

Abstract LB076: Association between regional COVID-19 hospitalizations and treatment delays amongst confirmed cancer patients in England, UK

Abstract Introduction: The COVID-19 pandemic has had substantial impacts on cancer services. National Cancer Waiting Times (CWT) targets in England stipulate that individuals referred from primary care for suspected cancer must receive treatment for any confirmed cancer within 62 days of referral. This analysis aimed to broadly quantify the association between COVID-19 hospitalizations by England region, and the proportion of confirmed cancer patients breaching the 62-day target in that region a month later, during the first wave of COVID-19 in England. Methods: CWT data were retrospectively obtained from all 135 clinical subregions of the National Health Service (NHS) in England, for the 6-month period from April to September 2020 inclusive. Subregion data were then grouped by each of the seven regions of England: London; South East England; South West England; East of England; the Midlands; North West England; and North East England &amp; Yorkshire. The mean number of monthly cases of confirmed cancer that waited more than 62 days from referral for their treatment (CWT breaches) was calculated amongst subregions within each region, inclusive of all cancer types. These 62-day primary care referrals represent around 73% of all treated cancers. These data were entered into linear regression models for each region, alongside daily UK Government data on numbers of patients in hospital with suspected COVID-19 within each region, with a 30-day lag applied (e.g. CWT breaches that occurred in June were plotted against COVID-19 hospitalization data from May). Results: The regression models showed that regional COVID-19 hospitalizations were significantly positively associated with 62-day CWT breaches the following month, for all regions except for London (all significant at the p&amp;lt;0.01 level). The association also approached significance for the London region (p=0.053). Adjustments for the size of each region produced standardised estimates of the average number of COVID-19 hospitalizations per subregion associated with a 1% absolute decrease in the proportion of 62-day referrals meeting the target: 15 in South East England, 20 in South West England, 17 in the East of England, 17 in the Midlands, 17 in the North West of England, 19 in the North East of England &amp; Yorkshire, and 35 in London. Regional findings for London should be interpreted with caution, due to its characteristics as both the epicenter of the first wave, and as an area with high density of hospitals and cancer centers. Conclusion: Higher rates of regional hospitalizations for suspected COVID-19 during England's initial wave of SARS-CoV-2 were associated with increased delays to cancer treatments across most England regions. It should be noted that CWT breaches do not necessarily translate directly into clinical harm, due to clinical risk prioritization strategies that were deployed during the initial wave of COVID-19. Citation Format: Louis Fox, Ajay Aggarwal, Richard Sullivan, Kate Haire, Arnie Purushotham, James Spicer, Sophie Papa, Anne Rigg, Saoirse Dolly, Mieke Van Hemelrijck. Association between regional COVID-19 hospitalizations and treatment delays amongst confirmed cancer patients in England, UK [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB076.

Effects of climatic factors and particulate matter on Rotavirus A infections in Cheonan, Korea, in 2010-2019.

Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.

Acute community ophthalmology services provided by independent prescribing optometrists supporting hospital eye services during the COVID-19 outbreak

BackgroundSpecialised Independent Prescribing (IP) community optometrists provided acute eye care during the COVID-19 crisis ensuring that over-stretched hospital emergency eye care was supported, therefore local overall urgent eye care provision was not affected. Subjects/methodsNumber of cases seen by hospital Rapid Access Clinic (RAC) between January 2020 and June 2020 were compared to number of cases seen by IP optometrists in community Acute Primary Care Ophthalmology Service (APCOS) during the same time period. Specifically, comparisons were made between the number of cases seen in RAC and the number of cases seen by APCOS during the period before COVID-19 emergency (January–March 2020) and for a similar timeframe thereafter (April–June 2020). Numbers treated by APCOS alone and those referred to RAC were also determined. The change in case numbers between the different healthcare settings was also studied. ResultsIncrease in cases seen by APCOS between April (n = 391) and June (n = 641). Number of cases seen by RAC declined from 652 in March to 372 in April, increasing to 610 by June. This was still below maximum number of monthly cases seen by RAC pre-lockdown in January (861). Most of the cases seen by APCOS were managed in the community with 4% referred to RAC. ConclusionsOphthalmology services delivered by IP specialised optometrists can safely and efficiently treat and manage the vast majority of urgent cases and mitigate the reduced capacity within hospital emergency eye clinics. Our experience provides insights into care pathways for urgent eye cases in the future.

Relationship between influenza and dengue outbreaks, and subsequent bacterial sepsis in French Guiana: A time series analysis.

Background: Influenza has been shown to increase the risk for severe bacterial infection, in the tropics the seasonality of influenza epidemics is less marked, and this may not be the case. Dengue is often followed by prolonged asthenia and some physicians hypothesized increased susceptibility to infections based on anecdotal observations.Design and Methods: Time series of influenza and dengue surveillance were confronted bacterial sepsis admissions to test the hypotheses. Monthly surveillance data on influenza and dengue and aggregated sepsis data in Cayenne hospital were matched between 24/10/2007 and 27/09/2016. An ARIMA (1,0,1) model was used.Results The series of the number of monthly cases of sepsis was positively associated with the monthly number of cases of influenza at time t (β=0.001, p=0.0359). Forecasts were imperfectly correlated with sepsis since influenza is not the only risk factor for sepsis. None of the ARIMA models showed a significant link between the dengue series and the sepsis series.Conclusions: There was thus no link between dengue epidemics and sepsis, but it was estimated that for every 1,000 cases of flu there was one additional case of sepsis. In this tropical setting, influenza was highly seasonal, and improved vaccination coverage could have benefits on sepsis.Significance for public healthSimultaneous infections may have complex consequences ranging from synergistic, neutral or antagonistic. Dengue fever and influenza cause repeated epidemics and may have consequences on the host’s immune response. Hypothesizing that an infection by dengue or influenza could increase the risk of bacterial infection we showed that there was no relation between dengue and sepsis, but that there was a relation between influenza and sepsis. Despite the tropical setting of French Guiana, the highly seasonal pattern of influenza suggests the vaccine reimbursement window should be extended.