Monthly Incidence Rate Research Articles

Population-based study and a scoping review for the epidemiology and seasonality in and effect of weather on Bell\u2019s palsy

The association between weather-related variables or seasons and the development of Bell’s palsy (BP) is controversial. This study aimed to evaluate the incidence and clinical characteristics of BP and assess the effects of meteorological factors on seasonal and monthly incidence. This retrospective population-based study used data from the Korean Health Insurance claims database (NHICD) from 2010 to 2018, in which annual, seasonal, and monthly incidence rates and age and sex distributions were calculated. A multivariate linear regression and autoregressive integrated moving average (ARIMA) model was used to determine the association between the seasonal and monthly incidence of BP and meteorological factors, including average wind speed, temperature, relative humidity, and atmospheric pressure. We also conducted a scoping review of the literature on epidemiological and seasonality studies of BP in the past 30 years and summarized them in a table for easy comparison with other studies. In this study, the incidence rate of BP increased over 9 years (from 12.86 to 19.92 per 100,000 persons) and was the highest in patients in their 60s (31.6/100,000 persons). The seasonal incidence of BP was the highest in autumn and showed a significant difference compared with spring (coefficient − 0.318, p = 0.003) and summer (coefficient − 0.463, p < 0.001), adjusting the year. In the ARIMA analysis, the autocorrelation of the monthly and seasonal lag in the raw data disappeared after adjustment of the seasonal (or monthly) and longitudinal changes, indicating no additional trends outside the seasonal (or monthly) longitudinal changes. The seasonal and monthly incidence of BP was related to low temperature (p = 0.002), high atmospheric pressure (p = 0.034), and low relative humidity (p < 0.001) in the multivariate linear regression. In contrast, in the ARIMA analysis, after adjusting for seasonality, month, and trends, there were no significant meteorological factors associated with the monthly or seasonal incidence rate. In the past 30 years, 12 studies have reported on the prevalence or incidence of BP, and 14 have reported on the relationship between seasons, weather, and incidence. These results indicate that BP is more common among the elderly, and the incidence of BP is increasing due to an aging society, increased medical accessibility, and lifestyle changes. The data also indicate that the onset of BP is associated with low temperature and humidity; however, in the climate zone with extreme temperature and humidity differences between the coldest and hottest months, it is assumed that the marked decrease in temperature (autumn) has more influence on the outbreak of BP than does the actual cold temperature (winter).

ASSESSING RISK FACTORS OF MALARIA IN LAKHIMPUR DISTRICT OF ASSAM

Malaria is a life-threatening parasitic disease transmitted from person to person through the bite of a female Anopheles mosquito. The transmission of malaria can be determined by climatic and host factors. The objective of this paper is to trace the host factors of malaria incidence and also to determine the relationship between climatic factors and malaria incidence in Lakhimpur district of Assam. In order to examine the association between monthly malaria incidence rates and climatic variables, Pearson correlation analysis has been used. Also, Chi-square test for independence of attributes is performed to trace the host factors of malaria incidence. A uctuating trend was observed for reported malaria cases during the years 2000-2011. Both positive and negative correlation have occurred between climatic variable and MIR. Also, we have observed that male is more affected by malaria incidence than female. Among the age groups, the age group 15-39 years was found most affected age group than other age groups. After Chi-square test for independence of attributes we reveal that malaria depends on sex and age. SUMMARY: From our study, we suggest that even if the climatic factors play a primary role for transmission of malaria, sex and age are other important risk factors in characterizing malaria incidence in the district.

The impacts of ambient temperature and ultraviolet radiation on the incidence of herpes zoster: An ecological study in Taiwan.

The aim of the study was to examine the relationship between ambient temperature, ultraviolet radiation, and the development of herpes zoster in Taiwan. An ecological study was conducted to analyse the database of the Taiwan National Health Insurance Programme. Participants aged ≥20years with newly diagnosed herpes zoster between 2003 and 2012 were selected for analysis. The monthly incidence rate of herpes zoster was measured between 2003 and 2012. Monthly average ambient temperature in Celsius (°C) between 2003 and 2012 was measured according to the official database of the Central Weather Bureau in Taiwan. Monthly accumulated ultraviolet radiation (MJm-2 ) between 2003 and 2012 was measured according to the official database of the Environmental Protection Administration in Taiwan. The overall incidence rates of herpes zoster ranged from 2.54 to 5.67 per 10000 persons per month from 2003 to 2012.The monthly average ambient temperature was higher and the monthly accumulated ultraviolet radiation was stronger from May to October. The incidence rates of herpes zoster seemed to be high during the period of high ambient temperature and strong ultraviolet radiation (from May to October).Whenever ambient temperature increased 1°C per month, the incidence rate of herpes zoster increased by 0.072 per 10,000 persons per month. Whenever ultraviolet radiation increased 1MJm-2 per month, the incidence rate of herpes zoster increased by 0.313 per 10000 persons per month. There is a significant association between ambient temperature, ultraviolet radiation, and the development of herpes zoster in Taiwan. The incidence rate of herpes zoster is high during the period of high ambient temperature and strong ultraviolet radiation. Low ambient temperature and weak ultraviolet radiation might be beneficial for the prevention of herpes zoster.

Increased Isolation of Pathogens After Resin-Containing Blood Culture Bottle Implementation

Background: Resin-containing blood culture bottles (RBB) are used to increase the isolation of microorganisms by binding antimicrobials in sampled blood. Since RBB implementation in April 2018, our infection preventionists noted an increase in positive blood cultures on routine surveillance. Objective: To describe the change in bacterial isolation post-RBB implementation. Methods: All positive blood culture sets drawn in adult inpatient units or the emergency room between October 2017 and September 2018 and their associated organisms were obtained from the hospital laboratory database. Then, regardless of central-line placement or “present on admission” designation, the 2019 NHSN surveillance definitions for laboratory-confirmed bloodstream infection (LCBI-1 and LCBI-2) were applied to categorize all positive cultures as “common commensals” (CCs) or pathogens. A univariate analysis was performed using the Mantel-Haenszel χ2 test (OpenEpi version 3.01). Results: Although the number of monthly blood cultures drawn remained effectively stable before and after implementation (pre-RBB median, 3,512.5; post-RBB median, 3,626), the rate ratio of positive cultures increased by 1.36 times: pre-RBB median, 127 sets per month and post-RBB median, 172.5 sets per month (χ2 = 5.785; P = .008). The rate ratio of pathogen-containing cultures increased by 1.40 times (pre-RBB median, 98 sets per month and post-RBB median, 137.5 sets per month; χ&amp;sup2; = 5.615; P = .009) with only a 1.24 increase in CCs (pre-RBB median, 29 and post-RBB median, 36; χ&amp;sup2; = 0.553; P = .229) (Fig. 1). Conclusions: After RBB implementation, the monthly incidence rate of pathogen-containing sets increased. Additionally, the increase in these sets as well as of overall positive blood cultures was statistically significant. Current literature on RBBs does not suggest preferential increased isolation of pathogens. Further study is needed to determine whether our findings are related to blood-culturing practices or the RBBs themselves.Funding: NoneDisclosures: None

Influence of Meteorological Factors on HFMD and Construction of Prediction Model in Sichuan Province

To analyze the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Sichuan Province from 2013 to 2019. To study the correlation between meteorological factors and the incidence of HFMD and construct a prediction model. The HMFD surveillance data and meteorological data from 2013 to 2019 in Sichuan Province were collected through the Chinese Center for Disease Control and Prevention and the China Meteorological data Network. Spearman correlation was used to analyze the relationship between HFMD incidence and meteorological factors. Multiple regression model and support vector regression (SVR) model were used to construct HFMD incidence prediction models respectively. A total of 615 840 cases of HFMD and 81 deaths were reported from 2013 to 2019. The average annual incidence rate was 107.31/105, and the mortality rate was 0.16/106. Spearman correlation analysis showed that the monthly incidence rate of HFMD was correlated with monthly average relative humidity (r=0.342), monthly average temperature (r=0.284), monthly average water vapor pressure (r=0.304) and monthly average days of precipitation (r=0.259). The prediction effect of the SVR model (R2=0.836) was better than the multiple regression model (R2=0.375). The SVR model provided a good fit to the monthly incidence of HFMD from 2013 to 2018, and can predict the peak incidence of HFMD in 2019. Relative humidity has the greatest influence on the incidence of HFMD. The fitting value of SVR model is in good agreement with the actual value, which is valuable in predicting the incidence of HFMD in Sichuan Province.

Forecasting the monthly incidence rate of brucellosis in west of Iran using time series and data mining from 2010 to 2019.

The identification of statistical models for the accurate forecast and timely determination of the outbreak of infectious diseases is very important for the healthcare system. Thus, this study was conducted to assess and compare the performance of four machine-learning methods in modeling and forecasting brucellosis time series data based on climatic parameters. In this cohort study, human brucellosis cases and climatic parameters were analyzed on a monthly basis for the Qazvin province-located in northwestern Iran- over a period of 9 years (2010-2018). The data were classified into two subsets of education (80%) and testing (20%). Artificial neural network methods (radial basis function and multilayer perceptron), support vector machine and random forest were fitted to each set. Performance analysis of the models were done using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Root Error (MARE), and R2 criteria. The incidence rate of the brucellosis in Qazvin province was 27.43 per 100,000 during 2010-2019. Based on our results, the values of the RMSE (0.22), MAE (0.175), MARE (0.007) criteria were smaller for the multilayer perceptron neural network than their values in the other three models. Moreover, the R2 (0.99) value was bigger in this model. Therefore, the multilayer perceptron neural network exhibited better performance in forecasting the studied data. The average wind speed and mean temperature were the most effective climatic parameters in the incidence of this disease. The multilayer perceptron neural network can be used as an effective method in detecting the behavioral trend of brucellosis over time. Nevertheless, further studies focusing on the application and comparison of these methods are needed to detect the most appropriate forecast method for this disease.

Epidemiological Features of Human Brucellosis in Iran (2011-2018) and Prediction of Brucellosis with Data-Mining Models.

Brucellosis is known as the major zoonotic disease. We aimed to compare the performance of some data-mining models in predicting the monthly brucellosis cases in Iran. Population-based cohort study. Three data mining techniques including the Support Vector Machine (SVM), Multivariate Adaptive Regression Splines (MARS), and Random Forest (RF) besides to one classic model including Auto-Regressive Integrated Moving Average (ARIMA) was used to predict the monthly incidence of brucellosis in Iran during 2011-2018. We used several criteria (root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2) and intra-class correlation coefficient (ICC) for appraising the accuracy of prediction and performance of our models. All analysis was done using free statistical software of R3.4.0 RESULTS: Overall 118867 cases (with a mean age of 34.01±1.65 yr) of brucellosis were observed and seven-year incidence rate of brucellosis in Iran was 21.78 (95% CI: 21.66, 21.91). The majority of patients (58.84%) were male and 25-29 yr old. The first three provinces with the highest incidence rate of brucellosis included the following; Kurdistan (71.39 per 100000), Lorestan (68.09 per 100000) and Hamadan (56.24 per 100000). Brucellosis was more common in males, 25-29 aged yr, western provinces and spring months. The disease had a decreasing trend in the last years. MARS model was more appropriate rather than data mining models for prediction of monthly incidence rate of brucellosis.

Evidence for heterogeneity in China\u2019s progress against pulmonary tuberculosis: uneven reductions in a major center of ongoing transmission, 2005\u20132017

BackgroundChina contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health.MethodsWe estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level.ResultsFrom 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28–4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61–3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors.ConclusionsWhile PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting.

Forecasting models of infections due to carbapenem-resistant Gram-negative bacteria in an intensive care unit in an endemic area.

The aim of this study was to forecast the monthly incidence rates of infections [infections/1000 bed-days (IBD)] due to carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Pseudomonas aeruginosa (CRPA), carbapenem-resistant Acinetobacter baumannii (CRAB) and total carbapenem-resistant Gram-negative bacteria (CRGNB) in an endemic intensive care unit (ICU) during the subsequent year (December 2016-December 2017) following the observational period. A 52-month observational period (August 2012-November 2016) was used. Two forecasting models, including a simple seasonal model for CRGNB, CRKP and CRPA and Winters' additive model for CRAB infections, were applied. The models predicted the highest infection rates for CRKP, CRAB and CRGNB in January and September 2017 (23.8/23.4, 24.6/28.5 and 46.8/46.7 IBD, respectively) and for CRPA in February and March 2017 (8.3 and 7.9, respectively). The highest observed rates for CRKP, CRAB and CRGNB were indeed in January and September 2017 (25.6/19.0, 34.2/23.8 and 59.8/42.8 IBD, respectively); and for CRPA in February and March of the same year (15.2 and 12.7, respectively). The increased rates may be associated with personnel's annual work programme and behavioural factors. Forecasting models in endemic ICUs may assist in implementation strategies for infection control measures.

Use of Routine Health Information System Data to Evaluate Impact of Malaria Control Interventions in Zanzibar, Tanzania from 2000 to 2015

BackgroundImpact evaluations allow countries to assess public health gains achieved through malaria investments. This study uses routine health management information system (HMIS) data from Zanzibar to describe changes in confirmed malaria incidence and impact of case management and vector control interventions during 2000–2015. MethodsHMIS data from 129 (82%) public outpatient facilities were analyzed using interrupted time series models to estimate the impact of artemisinin-based combination therapy (ACT), indoor residual spray, and long-lasting insecticidal nets. Evaluation periods were defined as pre-intervention (January 2000 to August 2003), ACT-only (September 2003 to December 2005) and ACT plus vector control (2006–2015). FindingsAfter accounting for climate, seasonality, diagnostic testing rates, and outpatient attendance, average monthly incidence of confirmed malaria showed no trend over the pre-intervention period 2000–2003 (incidence rate ratio (IRR) 0.998, 95% CI 0.995–1.000). During the ACT-only period (2003–2005), the average monthly malaria incidence rate declined compared to the pre-intervention period, showing an overall declining trend during the ACT-only period (IRR 0.984, 95% CI 0.978–0.990). There was no intercept change at the start of the ACT-only period (IRR 1.081, 95% CI 0.968–1.208), but a drop in intercept was identified at the start of the ACT plus vector control period (IRR 0.683, 95% CI 0.597–0.780). During the ACT plus vector control period (2006–2015), the rate of decline in average monthly malaria incidence slowed compared to the ACT-only period, but the incidence rate continued to show an overall slight declining trend during 2006–2015 (IRR 0.993, 95% CI 0.992–0.994). InterpretationThis study presents a rigorous approach to the use of HMIS data in evaluating the impact of malaria control interventions. Evidence is presented for a rapid decline in malaria incidence during the period of ACT roll out compared to pre-intervention, with a rapid drop in malaria incidence following introduction of vector control and a slower declining incidence trend thereafter.

Application of a hybrid model in predicting the incidence of tuberculosis in a Chinese population.

Objective: To investigate suitable forecasting models for tuberculosis (TB) in a Chinese population by comparing the predictive value of the autoregressive integrated moving average (ARIMA) model and the ARIMA-generalized regression neural network (GRNN) hybrid model.Methods: We used the monthly incidence rate of TB in Lianyungang city from January 2007 through June 2016 to construct a fitting model, and we used the incidence rate from July 2016 to December 2016 to evaluate the forecasting accuracy. The root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE) and mean error rate (MER) were used to assess the performance of these models in fitting and forecasting the incidence of TB.Results: The ARIMA (10, 1, 0) (0, 1, 1)12 model was selected from plausible ARIMA models, and the optimal spread value of the ARIMA-GRNN hybrid model was 0.23. For the fitting dataset, the RMSE, MAPE, MAE and MER were 0.5594, 11.5000, 0.4202 and 0.1132, respectively, for the ARIMA (10, 1, 0) (0, 1, 1)12 model, and 0.5259, 11.2181, 0.3992 and 0.1075, respectively, for the ARIMA-GRNN hybrid model. For the forecasting dataset, the RMSE, MAPE, MAE and MER were 0.2805, 8.8797, 0.2261 and 0.0851, respectively, for the ARIMA (10, 1, 0) (0, 1, 1)12 model, and 0.2553, 5.7222, 0.1519 and 0.0571, respectively, for the ARIMA-GRNN hybrid model.Conclusions: The ARIMA-GRNN hybrid model was shown to be superior to the single ARIMA model in predicting the short-term TB incidence in the Chinese population, especially in fitting and forecasting the peak and trough incidence.

Joinpoint regression model analysis on epidemiological trends of hand, foot and mouth disease in Guangdong, 2008–2017

ObjectiveTo analyze the change in the epidemiological trends of hand, foot and mouth disease (HFMD)in Guangdong province. MethodsThe incidence data of HFMD in Guangdong during 2008–2017 were collected from National Notifiable Infectious Disease Reporting Information System, and population data in Guangdong during this period were collected from Guangdong Statistical Yearbook. The epidemiological trends of HFMD were analyzed by using Joinpoint regression model. ResultsThe incidence trend of HFMD began to change in 2012. From 2008 to 2012, the incidence rate of HFMD increased sharply (β1＝72.552, P＝0.001), and from 2012 to 2017, the incidence increased with slight fluctuation, the difference had no significance (β2＝6.647, P＝0.588). The incidence change trend was not parallel between males and females, the change extent in males exceeded that in females. The incidence increase sharply from January to May and peaked in May, then it began to decline, the monthly annual percent change (APC) was 138.33%(P＝0.002). From May to December, the incidence of HFMD declined slightly, the monthly APC was –19.19% (P＝0.002). Two joinpoints were detected among the trend change of the monthly incidence rate of HFMD in 2008、2013 and 2017 years respectively and only one joinpoint was found in the other years. The age specific incidence was characterized by high level in age group from 0– to 2– years (Age group APC＝17.32%, P＝0.001), decrease rapidly from age group 2– years to 15–19 years (APC＝−44.81%, P＝0.000), and keeping at very low level from age group 15–19 years to ≥85 years (APC＝−2.66%, P＝0.148). ConclusionThe annual incidence of HFMD in Guangdong first showed a rapid increase and then slight increase with fluctuation during 2008–2017. The trend change of annual incidence rate was significantly different between male and female. Two models were found in the trend change of monthly incidence rate and there were significant seasonal variations. Very most of the HFMD case were among young children, so they were the key object for prevention and control. Prevention and control measures should be more targeted.

Association Between Cancer Incidence and Mortality in Web-Based Data in China: Infodemiology Study.

BackgroundCancer poses a serious threat to the health of Chinese people, resulting in a major challenge for public health work. Today, people can obtain relevant information from not only medical workers in hospitals, but also the internet in any place in real-time. Search behaviors can reflect a population’s awareness of cancer from a completely new perspective, which could be driven by the underlying cancer epidemiology. However, such Web-retrieved data are not yet well validated or understood.ObjectiveThis study aimed to explore whether a correlation exists between the incidence and mortality of cancers and normalized internet search volumes on the big data platform, Baidu. We also assessed whether the distribution of people who searched for specific types of cancer differed by gender. Finally, we determined whether there were regional disparities among people who searched the Web for cancer-related information.MethodsStandard Boolean operators were used to choose search terms for each type of cancer. Spearman’s correlation analysis was used to explore correlations among monthly search index values for each cancer type and their monthly incidence and mortality rates. We conducted cointegration analysis between search index data and incidence rates to examine whether a stable equilibrium existed between them. We also conducted cointegration analysis between search index data and mortality data.ResultsThe monthly Baidu index was significantly correlated with cancer incidence rates for 26 of 28 cancers in China (lung cancer: r=.80, P<.001; liver cancer: r=.28, P=.016; stomach cancer: r=.50, P<.001; esophageal cancer: r=.50, P<.001; colorectal cancer: r=.81, P<.001; pancreatic cancer: r=.86, P<.001; breast cancer: r=.56, P<.001; brain and nervous system cancer: r=.63, P<.001; leukemia: r=.75, P<.001; Non-Hodgkin lymphoma: r=.88, P<.001; Hodgkin lymphoma: r=.91, P<.001; cervical cancer: r=.64, P<.001; prostate cancer: r=.67, P<.001; bladder cancer: r=.62, P<.001; gallbladder and biliary tract cancer: r=.88, P<.001; lip and oral cavity cancer: r=.88, P<.001; ovarian cancer: r=.58, P<.001; larynx cancer: r=.82, P<.001; kidney cancer: r=.73, P<.001; squamous cell carcinoma: r=.94, P<.001; multiple myeloma: r=.84, P<.001; thyroid cancer: r=.77, P<.001; malignant skin melanoma: r=.55, P<.001; mesothelioma: r=.79, P<.001; testicular cancer: r=.57, P<.001; basal cell carcinoma: r=.83, P<.001). The monthly Baidu index was significantly correlated with cancer mortality rates for 24 of 27 cancers. In terms of the whole population, the number of women who searched for cancer-related information has slowly risen over time. People aged 30-39 years were most likely to use search engines to retrieve cancer-related knowledge. East China had the highest Web search volumes for cancer.ConclusionsSearch behaviors indeed reflect public awareness of cancer from a different angle. Research on internet search behaviors could present an innovative and timely way to monitor and estimate cancer incidence and mortality rates, especially for cancers not included in national registries.

Invasive pneumococcal diseases in children and adults before and after introduction of the 10-valent pneumococcal conjugate vaccine into the Austrian national immunization program.

BackgroundIn February 2012 the ten-valent pneumococcal conjugate vaccine (PCV10) with a 2+1 doses schedule (3, 5, 12 or 14 months of age) without catch-up vaccination was introduced in Austria. We assessed direct and indirect vaccine effects on invasive pneumococcal disease (IPD) by a population-based intervention study.MethodsThe study period was divided into pre- (2009–2011) and post-period (2013–2017, February), regarding 2012 as transition year. Outcomes were defined as PCV10 ST-IPD, the PCV10-related ST 6A and 19A IPD and non-PCV10 excluding ST 6A-/19A-IPD (NVT-IPD). We used national surveillance data and compared average monthly incidence rate (IR) between pre- and post-period among <5, 5–49 and ≥50 years old. Additionally, for the 5–49 and ≥50 years old, and the 50–59 and ≥60 years old, we analyzed monthly incidence data of the pre-, post-period, and estimated trend and level changes by using a segmented time-series regression.ResultsThe PCV-10 IPD was reduced by 58% (95% CI: 30%; 74%) and 67% (95% CI: 32%; 84%) among <5 and ≥50 years old; the reduction in ≥60 years was 71% (95% CI: 36%; 88%). There were no significant changes in the pre-post-rate or incidence trend of NVT-IPD in the <5 and ≥50 years old. ST-specific analyses revealed no ST 6A- and ST 19A IPD decline in any age-group, and a ST 8 IPD increase among ≥50 years old (IR ratio: 3.5; 95% CI: 1.7; 7.2). We found no vaccine effects among 5–49 years old.ConclusionsOur study adds to the evidence on direct and indirect protection of a childhood PCV10 vaccine program. Elderlies seem to benefit the most. Findings did not support PCV 10 cross-protection, but indicate replacement at least for ST 8 among the ≥50 years old. Follow-up analyses of IPD surveillance data are needed to fully characterize the magnitude of serotype replacement and further vaccine-attributable IPD reduction with time.

The association of cellulitis incidence and meteorological factors in Taiwan.

Cellulitis is a common infection of the skin and soft tissue. Susceptibility to cellulitis is related to microorganism virulence, the host immunity status and environmental factors. This retrospective study from 2001 to 2013 investigated relationships between the monthly incidence rate of cellulitis and meteorological factors using data from the Taiwanese Health Insurance Dataset and the Taiwanese Central Weather Bureau. Meteorological data included temperature, hours of sunshine, relative humidity, total rainfall and total number of rainy days. In otal, 195 841 patients were diagnosed with cellulitis and the incidence rate was strongly correlated with temperature (γS = 0.84, P &lt; 0.001), total sunshine hours (γS = 0.65, P &lt; 0.001) and total rainfall (γS = 0.53, P &lt; 0.001). The incidence rate of cellulitis increased by 3.47/100 000 cases for every 1° elevation in environmental temperature. Our results may assist clinicians in educating the public of the increased risk of cellulitis during warm seasons and possible predisposing environmental factors for infection.

Spatial-temporal characteristics and the epidemiology of haemorrhagic fever with renal syndrome from 2007 to 2016 in Zhejiang Province, China

Zhejiang Province is one of the six provinces in China that has the highest incidence of haemorrhagic fever with renal syndrome (HFRS). Data on HFRS cases in Zhejiang Province from January 2007 to July 2017 were obtained from the China Information Network System of Disease Prevention and Control. Joinpoint regression analysis was used to observe the trend of the incidence rate of HFRS. The monthly incidence rate was predicted by autoregressive integrated moving average(ARIMA) models. Spatial autocorrelation analysis was performed to detect geographic clusters. A multivariate time series model was employed to analyze heterogeneous transmission of HFRS. There were a total of 4,836 HFRS cases, with 15 fatal cases reported in Zhejiang Province, China in the last decade. Results show that the mean absolute percentage error (MAPE) of the modelling performance and the forecasting performance of the ARIMA model were 27.53% and 16.29%, respectively. Male farmers and middle-aged patients account for the majority of the patient population. There were 54 high-high clusters and 1 high-low cluster identified at the county level. The random effect variance of the autoregressive component is 0.33; the spatio-temporal component is 1.30; and the endemic component is 2.45. According to the results, there was obvious spatial heterogeneity in the endemic component and spatio-temporal component but little spatial heterogeneity in the autoregressive component. A significant decreasing trend in the incidence rate was identified, and obvious clusters were discovered. Spatial heterogeneity in the factors driving HFRS transmission was discovered, which suggested that a targeted preventive effort should be considered in different districts based on their own main factors that contribute to the epidemics.

Application of Plan-Do-Check-Act(PDCA) cycle in reducing the incidence of hypoglycemia in inpatients diabetes management

Objective To apply the Plan-Do-Check-Act (PDCA) cycle in glucose management in inpatients with diabetes, in order to decrease the incidence of hypoglycemia and related complications. Methods 517 inpatients with diabetes were divided into 4 groups according to the quarter, the monthly incidence rates of hypoglycemia were collected.The association of monthly incidence of hypoglycemia with age (≥65 years), longer diabetic history (≥ 5 years), lower C-peptide (<0.370nmol/L), receiving combined regimen (basal insulin plus 3 doses of pre-prandial short-acting insulin) were analyzed.PDCA cycle was applied for hypoglycemia detection and etiology control in order to achieve quality improvement via effective glucose control measures.The χ2 test was used to analyze the incidence of the hypoglycemia in each group.The hypoglycemic incidence based on different characteristics, were also compared with the overall hypoglycemic incidences of all patients. Results The incidence of hypoglycemia was significantly reduced with the application of PDCA cycle in inpatients with diabetes, from 44.09% in the first quarter to 13.04% in the fourth quarter(χ2=32.815, P<0.001). The annual hypoglycemic incidence rate was 26.89%.The patients with low C-peptide or receiving combined regimen had significantly higher incidence rate of hypoglycemia (53.57% and 31.88%) as compared to general inpatients with diabetes(χ2=35.721, 7.105, all P<0.05). Conclusion The application of PDCA cycle can effectively decrease the incidence of hypoglycemia, and it can be a great asset for management of inpatients with diabetes. Key words: Quality control; Hypoglycemia; Insulin; Diabetes

Seasonal behavior and forecasting trends of tuberculosis incidence in Holy Kerbala, Iraq.

Pulmonary tuberculosis (PTB) remains major public health problem over the world. Cities witnessing religious event throughout of the year like Kerbala/Iraq require great efforts to minimize the incidence of deadly communicable diseases like TB. The aim of this study is to model the monthly incidence rates of PTB cases in Kerbala/Iraq. This is a retrospective study in which records of confirmed PTB patients whom they referred to the chest and respiratory illnesses center of Holy Kerbala governorate were obtained. Monthly registered new smear-positive PTB cases from January 2010 to December 2016 were analyzed. Seasonal autoregressive integrated moving average (SARIMA), SARIMA-exponential smoothing method (ETS), SARIMA-neural network autoregressive, and SARIMA-adaptive neuro-fuzzy inference system (SARIMA-ANFIS) were used for forecasting monthly incidence rate of TB in Kerbala, Iraq. Mean absolute percentage error, root mean square error, and mean absolute square error were used to compare the models, and Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to selected best model. The trend of PTB incidence showed a seasonal characteristic, with peaks in spring and winter. Predicted estimates using all models proposed to forecast the number of PTB cases from 2016 to 2018 showed that the PTB cases indicated marginal decrease trends and best forecasted in SARIMA-ANFIS model (the lower AIC and BIC values, 712.69 and 731.05, respectively). Seasonal characteristic of PTB incidence was observed with peaks during spring and winter. Forecasting of PTB incidence between the period 2016 and 2018 showed marginal decrease trends, and the best forecasting model was SARIMA-ANFIS model.

The additional benefit of residual spraying and insecticide-treated curtains for dengue control over current best practice in Cuba: Evaluation of disease incidence in a cluster randomized trial in a low burden setting with intensive routine control.

BackgroundAedes control interventions are considered the cornerstone of dengue control programmes, but there is scarce evidence on their effect on disease. We set-up a cluster randomized controlled trial in Santiago de Cuba to evaluate the entomological and epidemiological effectiveness of periodical intra- and peri-domiciliary residual insecticide (deltamethrin) treatment (RIT) and long lasting insecticide treated curtains (ITC).Methodology/Principal findingsSixty three clusters (around 250 households each) were randomly allocated to two intervention (RIT and ITC) and one control arm. Routine Aedes control activities (entomological surveillance, source reduction, selective adulticiding, health education) were applied in the whole study area. The outcome measures were clinical dengue case incidence and immature Aedes infestation. Effectiveness of tools was evaluated using a generalized linear regression model with a negative binomial link function.Despite significant reduction in Aedes indices (Rate Ratio (RR) 0.54 (95%CI 0.32–0.89) in the first month after RIT, the effect faded out over time and dengue incidence was not reduced. Overall, in this setting there was no protective effect of RIT or ITC over routine in the 17months intervention period, with for house index RR of 1.16 (95%CI 0.96–1.40) and 1.25 (95%CI 1.03–1.50) and for dengue incidence RR of 1.43 (95%CI 1.08–1.90) and 0.96 (95%CI 0.72–1.28) respectively. The monthly dengue incidence rate (IR) at cluster level was best explained by epidemic periods (Incidence Rate Ratio (IRR) 5.50 (95%CI 4.14–7.31)), the IR in bordering houseblocks (IRR 1.03 (95%CI 1.02–1.04)) and the IR pre-intervention (IRR 1.02 (95%CI 1.00–1.04)).ConclusionsAdding RIT to an intensive routine Aedes control programme has a transient effect on the already moderate low entomological infestation levels, while ITC did not have any effect. For both interventions, we didn’t evidence impact on disease incidence. Further studies are needed to evaluate impact in settings with high Aedes infestation and arbovirus case load.

Heatstroke Risk Predictions for Current and Near-Future Summers in Sendai, Japan, Based on Mesoscale WRF Simulations

The incidence of heatstroke has been increasing in Japan, and future climate change is likely to increase heatstroke risk. We therefore developed a method to quantify the spatial distribution of outdoor heatstroke risk and predicted future changes in this risk considering the predicted climate change in Sendai, Japan. Heatstroke risk was quantified by assessing hazard, vulnerability and exposure. Daily maximum wet-bulb globe temperature (WBGT) was selected as the hazard index. The distribution of WBGT was predicted by mesoscale meteorological simulations using the Weather Research and Forecasting (WRF) model. The relationship between daily maximum WBGT and the daily incidence rate was approximated by analyzing emergency transport data. This relationship was selected as the vulnerability index. Using the hazard and vulnerability indices, a spatial distribution of the monthly incidence rate was obtained. Finally, the total number of heatstroke patients per month was estimated by multiplying the monthly incidence rate by the population density. The outdoor heatstroke risk for August was then estimated for current (2000s) and near-future (2030s) climatic conditions in Sendai. WBGT at coastal areas in the 2030s increased owing to increases in humidity, while WBGT at inland areas increased owing to increases in air temperature. This increase in WBGT drove increases in heatstroke risk.