International Journal of Environmental Research and Public Health

Research

23 pages, 19742 KiB

Open AccessArticle

All-People-Test-Based Methods for COVID-19 Infectious Disease Dynamics Simulation Model: Towards Citywide COVID Testing

by Xian-Xian Liu, Jie Yang, Simon Fong, Nilanjan Dey, Richard C. Millham and Jinan Fiaidhi

Int. J. Environ. Res. Public Health 2022, 19(17), 10959; https://doi.org/10.3390/ijerph191710959 - 2 Sep 2022

Cited by 5 | Viewed by 1776

The conversion rate between asymptomatic infections and reported/unreported symptomatic infections is a very sensitive parameter for model variables that spread COVID-19. This is important information for follow-up use in screening, prediction, prognostics, contact tracing, and drug development for the COVID-19 pandemic. The model [...] Read more.

The conversion rate between asymptomatic infections and reported/unreported symptomatic infections is a very sensitive parameter for model variables that spread COVID-19. This is important information for follow-up use in screening, prediction, prognostics, contact tracing, and drug development for the COVID-19 pandemic. The model described here suggests that there may not be enough researchers to solve all of these problems thoroughly and effectively, and it requires careful selection of what we are doing and rapid sharing of results and models and optimizing modeling simulations with value to reduce the impact of COVID-19. Exploring simulation modeling will help decision makers make the most informed decisions. In order to fight against the “Delta” virus, the establishment of a line of defense through all-people testing (APT) is not only an effective method summarized from past experience but also one of the best means to effectively cut the chain of epidemic transmission. The effect of large-scale testing has been fully verified in the international community. We developed a practical dynamic infectious disease model-SETPG (A + I) RD + APT by considering the effects of the all-people test (APT). The model is useful for studying effects of screening measures and providing a more realistic modelling with all-people-test strategies, which require everybody in a population to be tested for infection. In prior work, a total of 370 epidemic cases were collected. We collected three kinds of known cases: the cumulative number of daily incidences, daily cumulative recovery, and daily cumulative deaths in Hong Kong and the United States between 22 January 2020 and 13 November 2020 were simulated. In two essential strategies of the integrated SETPG (A + I) RD + APT model, comparing the cumulative number of screenings in derivative experiments based on daily detection capability and tracking system application rate, we evaluated the performance of the timespan required for the basic regeneration number (R0) and real-time regeneration number (R0t) to reach 1; the optimal policy of each experiment is available, and the screening effect is evaluated by screening performance indicators. with the binary encoding screening method, the number of screenings for the target population is 8667 in HK and 1,803,400 in the U.S., including 6067 asymptomatic cases in HK and 1,262,380 in the U.S. as well as 2599 cases of mild symptoms in HK and 541,020 in the U.S.; there were also 8.25 days of screening timespan in HK and 9.25 days of screening timespan required in the U.S. and a daily detectability of 625,000 cases in HK and 6,050,000 cases in the U.S. Using precise tracking technology, number of screenings for the target population is 6060 cases in HK and 1,766,420 cases in the U.S., including 4242 asymptomatic cases in HK and 1,236,494 cases in the U.S. as well as 1818 cases of mild symptoms in HK and 529,926 cases in the U.S. Total screening timespan (TS) is 8.25~9.25 days. According to the proposed infectious dynamics model that adapts to the all-people test, all of the epidemic cases were reported for fitting, and the result seemed more reasonable, and epidemic prediction became more accurate. It adapted to densely populated metropolises for APT on prevention. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

15 pages, 2307 KiB

Open AccessArticle

Numerical Investigations through ANNs for Solving COVID-19 Model

by Muhammad Umar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Shumaila Javeed, Hijaz Ahmad, Sayed K. Elagen and Ahmed Khames

Int. J. Environ. Res. Public Health 2021, 18(22), 12192; https://doi.org/10.3390/ijerph182212192 - 20 Nov 2021

Cited by 9 | Viewed by 1709

Abstract

The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-Marquardt backpropagation (LMB), i.e., ANNs-LMB. The ANNs-LMB scheme is used in different variations of the sample data for training, validation, and testing with [...] Read more.

The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-Marquardt backpropagation (LMB), i.e., ANNs-LMB. The ANNs-LMB scheme is used in different variations of the sample data for training, validation, and testing with 80%, 10%, and 10%, respectively. The approximate numerical solutions of the COVID-19 spreading model have been calculated using the ANNs-LMB and compared viably using the reference dataset based on the Runge-Kutta scheme. The obtained performance of the solution dynamics of the COVID-19 spreading model are presented based on the ANNs-LMB to minimize the values of fitness on mean square error (M.S.E), along with error histograms, regression, and correlation analysis. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

24 pages, 2597 KiB

Open AccessArticle

National Holidays and Social Mobility Behaviors: Alternatives for Forecasting COVID-19 Deaths in Brazil

by Dunfrey Pires Aragão, Davi Henrique dos Santos, Adriano Mondini and Luiz Marcos Garcia Gonçalves

Int. J. Environ. Res. Public Health 2021, 18(21), 11595; https://doi.org/10.3390/ijerph182111595 - 4 Nov 2021

Cited by 10 | Viewed by 2287

Abstract

In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on disease reports of confirmed cases and deaths. First, [...] Read more.

In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on disease reports of confirmed cases and deaths. First, we use a one-variate model with the number of infected people as input data to forecast the number of deaths. This simple model is compared with a more robust deep learning multi-variate model that uses mobility and transmission rates (

R_{0}

,

R_{e}

) from a SEIRD model as input data. A principal components model of community mobility, generated by the principal component analysis (PCA) method, is added to improve the input features for the multi-variate model. The deep learning model architecture is an LSTM stacked layer combined with a dense layer to regress daily deaths caused by COVID-19. The multi-variate model incremented with engineered input features can enhance the forecast performance by up to 18.99% compared to the standard one-variate data-driven model. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

14 pages, 1008 KiB

Open AccessArticle

Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case

by Bo Lan, Perry Haaland, Ashok Krishnamurthy, David B. Peden, Patrick L. Schmitt, Priya Sharma, Meghamala Sinha, Hao Xu and Karamarie Fecho

Int. J. Environ. Res. Public Health 2021, 18(21), 11398; https://doi.org/10.3390/ijerph182111398 - 29 Oct 2021

Cited by 3 | Viewed by 1817

Abstract

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical [...] Read more.

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models. The objective of the present study was to use this approach to identify predictors of asthma exacerbations through the application of three multivariate methods: conditional random forest, conditional tree, and generalized linear model. Among seven potential predictor variables, we found five to be of significant importance using both conditional random forest and conditional tree: prednisone, race, airborne particulate exposure, obesity, and sex. The conditional tree method additionally identified several significant two-way and three-way interactions among the same variables. When we applied a generalized linear model, we identified four significant predictor variables, namely prednisone, race, airborne particulate exposure, and obesity. When ranked in order by effect size, the results were in agreement with the results from the conditional random forest and conditional tree methods as well as the published literature. Our results suggest that the open multivariate analytic capabilities provided by ICEES are valid in the context of an asthma use case and likely will have broad value in advancing open research in environmental and public health. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

12 pages, 468 KiB

Open AccessArticle

Utilisation of Skilled Birth Attendant in Low- and Middle-Income Countries: Trajectories and Key Sociodemographic Factors

by Tania Walker, Mulu Woldegiorgis and Jahar Bhowmik

Int. J. Environ. Res. Public Health 2021, 18(20), 10722; https://doi.org/10.3390/ijerph182010722 - 13 Oct 2021

Cited by 3 | Viewed by 2037

Abstract

Reducing the maternal mortality ratio (MMR) in low- and middle-income countries (LMICs) remains a huge challenge. Maternal mortality is mostly attributed to low coverage of maternal health services. This study investigated the trajectories and predictors of skilled birth attendant (SBA) service utilisation in [...] Read more.

Reducing the maternal mortality ratio (MMR) in low- and middle-income countries (LMICs) remains a huge challenge. Maternal mortality is mostly attributed to low coverage of maternal health services. This study investigated the trajectories and predictors of skilled birth attendant (SBA) service utilisation in LMIC over the past two decades. The data was sourced from standard demographic and health surveys which included four surveys on women with livebirth/s from selected countries from two regions with a pooled sample of 56,606 Indonesian and 63,924 Nigerian respondents. Generalised linear models with quasibinomial family of distributions were fitted to investigate the association between SBA utilisation and sociodemographic factors. Despite a significant improvement in the last two decades in both countries, the change was slower than hope for, and inconsistent. Women who received antenatal care were more likely to use an SBA service. SBA service utilisation was significantly more prevalent amongst literate women in Indonesia (AOR = 1.39, 95% CI: 1.24–1.54) and Nigeria (AOR = 1.41, 95% CI: 1.31–1.53) than their counterparts. The disparity based on geographic region and social factors remained significant over time. Given the significant disparities in SBA utilisation, there is a strong need to focus on community- and district-level interventions that aim at increasing SBA utilisation. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

12 pages, 626 KiB

Open AccessArticle

Concordance between Different Criteria for Self-Reported Physical Activity Levels and Risk Factors in People with High Blood Pressure in a Rural District in Bangladesh

by Fakir M. Amirul Islam, Jahar Bhowmik, Donny M. Camera, Ralph Maddison and Gavin W. Lambert

Int. J. Environ. Res. Public Health 2021, 18(19), 10487; https://doi.org/10.3390/ijerph181910487 - 6 Oct 2021

Cited by 1 | Viewed by 1691

Abstract

Self-reported assessment of physical activity (PA) is commonly used in public health research. The present study investigated the concordance of self-reported PA assessed using the global physical activity questionnaire (GPAQ) and two different measurement approaches. Participants (n = 307, aged 30–75 years [...] Read more.

Self-reported assessment of physical activity (PA) is commonly used in public health research. The present study investigated the concordance of self-reported PA assessed using the global physical activity questionnaire (GPAQ) and two different measurement approaches. Participants (n = 307, aged 30–75 years with hypertension) were recruited from a rural area in Bangladesh. We analyzed the difference between the World Health Organization (WHO) recommendations of more than 600 metabolic-equivalent time-minutes (MET-min) and the self-reported active hours, at least 2.5 h per week. Tests of sensitivity and specificity were conducted to determine concordance between the two measures. According to the WHO criteria, 255 (83%) participants were active more than 600 MET-min per week and 172 (56%) people were physically active 2.5 h or more per week, indicating a 27% difference in self-reported PA. The sensitivity, specificity, positive and negative predictive values and concordance between the two measures were 64%, 92%, 98%, 34% and 70%, respectively. Considering the WHO MET-min as the appropriate measure, 89 (35%) were false negative (FN). Older age, professionals and businesspersons were associated with a higher proportion of FN. There is a gap between self-reported PA, thus a better estimate of PA may result from combining two criteria to measure PA levels. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

15 pages, 369 KiB

Open AccessArticle

Knowledge of and Intention to Participate in Physical Activity Programs and Their Associated Sociodemographic Factors in People with High Blood Pressure in a Rural Area of Bangladesh: Initial Investigation from a Cluster Randomized Controlled Trial

by Fakir M. Amirul Islam, Mohammad Arzan Hosen, Mohammad Ariful Islam, Elisabeth A. Lambert, Bruce R. Thompson, Gavin W. Lambert and Ralph Maddison

Int. J. Environ. Res. Public Health 2021, 18(18), 9561; https://doi.org/10.3390/ijerph18189561 - 10 Sep 2021

Cited by 1 | Viewed by 2031

Abstract

This initial investigation aimed to investigate the knowledge of the health benefits of physical activity (PA) and attitudes towards participation in PA. The study recruited 307 people aged 30–75 years with hypertension as part of a cluster randomized controlled trial from a rural [...] Read more.

This initial investigation aimed to investigate the knowledge of the health benefits of physical activity (PA) and attitudes towards participation in PA. The study recruited 307 people aged 30–75 years with hypertension as part of a cluster randomized controlled trial from a rural area in Bangladesh. Of the 307 participants, 135 participated less than 2.5 h of physical activity per week, from which we collected data on attitudes toward PA. Regression analysis and Rasch analysis were used. More than 85% of homemakers, employees or businesspersons were willing to take part in PA. Based on the combined score from the knowledge and attitude items, 46% of people endorsed PA programs; proportions were higher in men than women (53% vs. 41%). After adjusting for covariates, men (odds ratio, 95% confidence interval (CI) 3.50, 1.72–7.11) compared to women and people with at least primary levels of schooling (OR 3.06, 95% CI, 1.27–7.38) compared with those with no education were more likely to organize or take part in any PA programs. People have positive attitudes towards PA but do not feel obligated to participate in PA programs. Future programs are needed to promote awareness and motivational interventions for PA, especially targeting women and people with low education levels, should be developed and implemented. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

13 pages, 727 KiB

Open AccessArticle

Factors Associated with Physical Activity among People with Hypertension in a Rural Area in Bangladesh: Baseline Data from a Cluster Randomized Control Trial

by Fakir M Amirul Islam

Int. J. Environ. Res. Public Health 2021, 18(14), 7365; https://doi.org/10.3390/ijerph18147365 - 9 Jul 2021

Cited by 4 | Viewed by 2332

Abstract

The health benefits of physical activity (PA) are well recognized, and PA levels vary in different populations. The study aimed to investigate PA levels and associated sociodemographic factors among people with hypertension in a rural area in Bangladesh. Baseline data were part of [...] Read more.

The health benefits of physical activity (PA) are well recognized, and PA levels vary in different populations. The study aimed to investigate PA levels and associated sociodemographic factors among people with hypertension in a rural area in Bangladesh. Baseline data were part of a cluster randomized controlled trial of 307 adults aged 30–75 years to study the effectiveness of PA and lifestyle changes in lowering blood pressure. The outcome variables were PA at work, commuter, recreation, metabolic equivalent task (MET)-minute per week and sitting time. Total 68 (22.1%) people participated in vigorous-intensity activity, 23 (7.5%) participated in moderate-intensity sports. Overall, 83% of people were physically active more than 600 MET-min. Women (OR 2.95, 95% CI, 1.36–6.39) compared to men, and people with no education (OR 4.47, 95% CI, 1.62–12.33) compared to people with secondary school certificates or above were less physically active. Of total PA, 63% were work-related, and 1% were recreation-related for women, and these figures were 55% and 3% for men. The study reports that vigorous-intensity PA is low, and recreation time is minimal. Routine PA, especially for women and people with low education levels, should be encouraged to increase PA to manage hypertension. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

17 pages, 3072 KiB

Open AccessArticle

Nine Months of COVID-19 Pandemic in Europe: A Comparative Time Series Analysis of Cases and Fatalities in 35 Countries

by David Meintrup, Martina Nowak-Machen and Stefan Borgmann

Int. J. Environ. Res. Public Health 2021, 18(12), 6680; https://doi.org/10.3390/ijerph18126680 - 21 Jun 2021

Cited by 13 | Viewed by 2981

Abstract

(1) Background: to describe the dynamic of the pandemic across 35 European countries over a period of 9 months. (2) Methods: a three-phase time series model was fitted for 35 European countries, predicting deaths based on SARS-CoV-2 incidences. Hierarchical clustering resulted in three [...] Read more.

(1) Background: to describe the dynamic of the pandemic across 35 European countries over a period of 9 months. (2) Methods: a three-phase time series model was fitted for 35 European countries, predicting deaths based on SARS-CoV-2 incidences. Hierarchical clustering resulted in three clusters of countries. A multiple regression model was developed predicting thresholds for COVID-19 incidences, coupled to death numbers. (3) Results: The model showed strongly connected deaths and incidences during the waves in spring and fall. The corrected case-fatality rates ranged from 2% to 20.7% in the first wave, and from 0.5% to 4.2% in the second wave. If the incidences stay below a threshold, predicted by the regression model (

R^{2} = 85.0 %

), COVID-19 related deaths and incidences were not necessarily coupled. The clusters represented different regions in Europe, and the corrected case-fatality rates in each cluster flipped from high to low or vice versa. Severely and less severely affected countries flipped between the first and second wave. (4) Conclusions: COVID-19 incidences and related deaths were uncoupled during the summer but coupled during two waves. Once a country-specific threshold of infections is reached, death numbers will start to rise, allowing health care systems and countries to prepare. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

13 pages, 3799 KiB

Open AccessArticle

Forecasting of Lung Cancer Incident Cases at the Small-Area Level in Victoria, Australia

by Win Wah, Rob G. Stirling, Susannah Ahern and Arul Earnest

Int. J. Environ. Res. Public Health 2021, 18(10), 5069; https://doi.org/10.3390/ijerph18105069 - 11 May 2021

Cited by 6 | Viewed by 2899

Abstract

Predicting lung cancer cases at the small-area level is helpful to quantify the lung cancer burden for health planning purposes at the local geographic level. Using Victorian Cancer Registry (2001–2018) data, this study aims to forecast lung cancer counts at the local government [...] Read more.

Predicting lung cancer cases at the small-area level is helpful to quantify the lung cancer burden for health planning purposes at the local geographic level. Using Victorian Cancer Registry (2001–2018) data, this study aims to forecast lung cancer counts at the local government area (LGA) level over the next ten years (2019–2028) in Victoria, Australia. We used the Age-Period-Cohort approach to estimate the annual age-specific incidence and utilised Bayesian spatio-temporal models that account for non-linear temporal trends and area-level risk factors. Compared to 2001, lung cancer incidence increased by 28.82% from 1353 to 1743 cases for men and 78.79% from 759 to 1357 cases for women in 2018. Lung cancer counts are expected to reach 2515 cases for men and 1909 cases for women in 2028, with a corresponding 44% and 41% increase. The majority of LGAs are projected to have an increasing trend for both men and women by 2028. Unexplained area-level spatial variation substantially reduced after adjusting for the elderly population in the model. Male and female lung cancer cases are projected to rise at the state level and in each LGA in the next ten years. Population growth and an ageing population largely contributed to this rise. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

14 pages, 3679 KiB

Open AccessArticle

A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic

by Faruq Abdulla, Zulkar Nain, Md. Karimuzzaman, Md. Moyazzem Hossain and Azizur Rahman

Int. J. Environ. Res. Public Health 2021, 18(9), 4491; https://doi.org/10.3390/ijerph18094491 - 23 Apr 2021

Cited by 14 | Viewed by 3829

Abstract

Background: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the [...] Read more.

Background: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-19, it is necessary to boost the knowledge about the effectiveness of such actions so that the policymakers take their country-based appropriate actions. This study generates evidence of taking the most impactful actions to combat COVID-19. Objective: In order to generate community-based scientific evidence, this study analyzed the outcome of COVID-19 in response to different control measures, healthcare facilities, life expectancy, and prevalent diseases. Methods: It used more than a hundred countries’ data collected from different databases. We performed a comparative graphical analysis with non-linear correlation estimation using R. Results: The reduction of COVID-19 cases is strongly correlated with the earliness of preventive initiation. The apathy of taking nationwide immediate precaution measures has been identified as one of the critical reasons to make the circumstances worse. There is significant non-linear relationship between COVID-19 case fatality and number of physicians (NCC = 0.22; p-value ≤ 0.001), nurses and midwives (NCC = 0.17; p-value ≤ 0.001), hospital beds (NCC = 0.20; p-value ≤ 0.001), life expectancy of both sexes (NCC = 0.22; p-value ≤ 0.001), life expectancy of female (NCC = 0.27; p-value ≤ 0.001), and life expectancy of male (NCC = 0.19; p-value ≤ 0.001). COVID-19 deaths were found to be reduced with increased medical personnel and hospital beds. Interestingly, no association between the comorbidities and severity of COVID-19 was found excluding asthma, cancer, Alzheimer’s, and smoking. Conclusions: Enhancing healthcare facilities and early imposing the control measures could be valuable to prevent the COVID-19 pandemic. No association between COVID-19 and other comorbidities warranted further investigation at the pathobiological level. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

16 pages, 1181 KiB

Open AccessArticle

Child Marriage and Adolescent Motherhood: A Nationwide Vulnerability for Women in Bangladesh

by Jahar Bhowmik, Raaj Kishore Biswas and Sorif Hossain

Int. J. Environ. Res. Public Health 2021, 18(8), 4030; https://doi.org/10.3390/ijerph18084030 - 12 Apr 2021

Cited by 17 | Viewed by 5080

Abstract

The persistently high prevalence of girl-child marriage and adolescent motherhood is a public health concern in Bangladesh. This study investigated the division-wise prevalence and the influence of education and religious affiliation on child marriage and adolescent motherhood among women in Bangladesh along with [...] Read more.

The persistently high prevalence of girl-child marriage and adolescent motherhood is a public health concern in Bangladesh. This study investigated the division-wise prevalence and the influence of education and religious affiliation on child marriage and adolescent motherhood among women in Bangladesh along with their consequences using 15,474 women aged 15–49 years from the Bangladesh Demographic and Health Survey 2017–18. Staggeringly, 82.5% women were married before 18, 43.1% were married before 15, and 61.8% gave birth before 18 years of age. Binary logistic regression models for the complex survey showed that girl-children with primary, secondary, and higher secondary or above education were 16% (95% CI: 0.69, 1.03), 32% (95% CI: 0.55, 0.84), and 87% (95% CI: 0.10, 0.17) less likely to get married <18 years of age, respectively, compared to the uneducated. Also, girl-children with secondary and higher education were 21 and 83% less likely to become adolescent mothers, respectively, than the uneducated. Women married during childhood (<18 years) and adolescent mothers were 36 and 55% less likely to continue studies after marriage, respectively, and expressed that they significantly preferred a late marriage. Policy interventions need to address culturally-laden social norms influenced by religious-related beliefs, especially in rural areas. Full article

(This article belongs to the Special Issue Application of Biostatistical Modelling in Public Health and Epidemiology)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Application of Biostatistical Modelling in Public Health and Epidemiology

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (12 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI