NEGATIVE BINOMIAL REGRESSION + AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELLING OF DENGUE DISEASE IN COLOMBO, SRI LANKA

2020 ◽  
Vol 64 (1) ◽  
pp. 103-112
Author(s):  
A. M. C. H. Attanayake ◽  
S. S. N. Perera ◽  
U. P. Liyanage
2021 ◽  
Author(s):  
Shelly Isnar ◽  
Mark Oremus

Governments implemented lockdowns and other physical distancing measures to stop the spread of SARS-CoV-2 (COVID-19). Resulting unemployment, income loss, poverty, and social isolation, coupled with daily reports of dire news about the COVID-19 pandemic, could serve as catalysts for increased self-harm deaths (SHD). This ecological study examined whether observed SHD counts were higher than predicted SHD counts during the pandemic period in the Canadian provinces of Alberta, British Columbia, Ontario, and Quebec. The study also explored whether SHD counts during the pandemic were affected by lockdown severity (measured using the lockdown stringency index [LSI]) and COVID-19 case numbers. We utilized publicly available SHD data from January 2018 through November 2020, and employed AutoRegressive Integrated Moving Average (ARIMA) modelling, to predict SHD during the COVID-19 period (March 21 to November 28, 2020). We used Poisson and negative binomial regression to assess ecological associations between the LSI and COVID-19 case numbers, controlling for seasonality, and SHD counts during the COVID-19 period. On average, observed SHD counts were lower than predicted counts during this period (p < 0.05 [except Alberta]). Additionally, LSI and COVID-19 case numbers were not statistically significantly associated with SHD counts.


2020 ◽  
Author(s):  
Imee Necesito ◽  
Jaewon Jung ◽  
Young Hye Bae ◽  
Soojun Kim ◽  
Hung Soo Kim

&lt;p&gt;Researchers have been looking for methods to prevent, control and provide lifelong protection to humans against dengue disease which is brought by the dengue-carrying mosquito called the Aedes Aegypti. However, such prevention, control and protection will best be aided by a dengue case prediction model. This study used the Negative Binomial Regression to forecast the dengue case incidence in Metro Manila, Philippines using principal components as explanatory variables. To ensure that the dengue cases are predictable, close returns plot (CRP) was performed.&amp;#160;&amp;#160; The logarithm of dengue case incidence which were assigned as response variables have showed higher value of variance over the mean which validates the use of negative binomial regression. Principal Component Analysis utilizing Nino 3.4 sea surface temperature (SST), precipitation and minimum temperature was used in the study. The acquired principal components (PC1, PC2, PC3 and PC4) were used as the explanatory variables for the negative binomial regression to calculate the number of the logarithm of dengue case incidence. However, to improve the calculated value of DHF cases in comparison to its actual value, residuals from the negative binomial regression were treated using moving average approach. The data used in this study were from 1994-2010 climatological data. Results for both negative binomial and moving average were combined to get the forecasted dengue incidence. Forecasted values showed a maximum of 12% difference from the actual DHF cases indicating a high forecasting performance. This study which focused on predicting the possible dengue incidence in the central districts of the Philippines&amp;#160; is believed to be essential to create plans of action to prevent and control this disease.&lt;/p&gt;


2021 ◽  
Vol 21 (3) ◽  
pp. e00523-e00523
Author(s):  
Abiyot Negash Terefe ◽  
Samuel Getachew Zewudie

Background: Coronavirus Disease 2019 (COVID-19) is affecting both lives of millions of people and the global economy of the world day by day. This study aimed to determine the trend of COVID-19 and its predictions in Ethiopia. Study Design: This study was conducted based on a time series design. Methods: The required data were collected from the Ethiopian COVID-19 monitoring platform beginning from the onset of the disease in the country until March 28, 2021. Furthermore, the auto-regressive integrated moving average models were used on daily-based time series. The Poisson and Negative Binomial regression were also employed to notice the effects of months on the transmission and disease-related human deaths. Results: The mean daily infection and death of COVID-19 in Ethiopia were 533.47±466.62 and 7.45±6.72, respectively. The peaks of infection and deaths in this country were in March, 2021, and August, 2020. In addition, the trend of daily new deaths (P=0.000) and infection (P=0.000) was significantly increasing. It is expected that around 10 million (8.6%) and 138,084.64 (0.12%) Ethiopians will be infected and die, respectively. Conclusions: The disease transmission and deaths vary from day to day and month to month. The highest peaks of COVID-19 infection and death were in March 2021 and August 2020. For the next end of August 2021, the COVID-19 daily new infection, new death, total case, and total death are expected to be increased. If this epidemic disease is not controlled, Ethiopia will face a severe shortage of hospitals, and the outbreak even becomes worse.


2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.


2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jun Heo ◽  
Won-Jun Choi ◽  
Seunghon Ham ◽  
Seong-Kyu Kang ◽  
Wanhyung Lee

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.


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