Forecast Incidence of Dengue Fever Cases in Fiji Utilizing Autoregressive Integrated Moving Average (ARIMA) Model

This paper examined the trend of dengue fever cases obtained from January 1995 to July 2017 from National Notifiable Disease Surveillance System (NNDSS) records, Fiji Ministry of Health and Medical Services. Box-Jenkins technique and model is applied to forecast incidence of dengue cases from August 2017 until December 2018. ARIMA model is proposed to forecast incidence of dengue fever in Fiji through Box-Jenkins approach. The Augmented Dickey Fullers test revealed that the time series data had unit root indicating non-stationary. The Autocorrelation and Partial Auto-correlation plots of the first order difference of the dengue fever data suggested parameters ARIMA(3,0,4) and ARIMA(3,1,4). The model ARIMA(3,0,4) was determined as the best fitted model which made a good forecasting performance in estimating the expected incidence dengue cases with lower Mean Absolute Percentage Error (MAPE) of 1148.319 and lower Bayesian Information Criterion (BIC) of 11.389. Finally, a forecast for dengue cases was obtained indicating the highest number of cases for December 2018 with estimated cases of 265. The ARIMA model method utilized in this paper forecasted the incidence trend of dengue fever cases effectively. Such results would be beneficial to health professionals and policy makers in planning of public health interventions and improvement to such disease epidemics. The efficacy of expected cases of dengue fever accomplish not only in detecting outbreaks, but also in delivering decision makers with a reasonable trend of the variability of future observations encompassing both historical, recent information and for evidence based decision making purposes

Hand, Foot and Mouth Disease in Vietnam: Epidemiology, Heart Rate Variability and Economic Burden

Over the last two decades, hand, foot and mouth disease (HFMD) has become a major clinical problem in Vietnam and the Asia-Pacific region. HFMD affects children, especially those under 5 years old, and has pandemic potential. Since 1997, there have been several outbreaks with severe clinical phenotypes, including brain stem encephalitis, attacking millions of children and causing thousands of deaths. Synthesizing data on epidemiology, etiology, disease pathophysiology and economic burden of this emerging infection remains essential to inform clinical management and health policy makers in prioritizing the development of intervention strategies. Using data from >56,000 hospitalized cases over an 11 year period, I described the spatial and temporal distribution of HFMD in Ho Chi Minh City, the main hotspot of HFMD in Vietnam. I found that the disease started in the west and then moved to the south-east and finally came back the west of the city. Results from a prospective multi-hospital based study conducted during 2015–2018 showed that of ~1200 enrolled patients, enterovirus A71 (EV-A71) was the most common HFMD pathogen detected, while coxsackievirus A6 (CV-A6) has emerged and replaced CV-A16 to become the second most common virus causing HFMD in Vietnam during the study period. Despite the emergence of other pathogens and the diversity of enterovirus serotypes (~20 serotypes) detected in HFMD patients, EV-A71 was the main cause of severe HFMD. Using long-term data synthesized as part of the research program, I also demonstrated for the first time that compared to EV-A71 subgenogroup B5, subgenogroup C4 was associated with more severe clinical phenotypes. Moreover, the predominance of subgenogroup C4 coincided with large, severe HFMD outbreaks in Vietnam (e.g. in 2011-12 and 2018). Collectively, the data suggest that an EV-A71 vaccine would be likely to substantially reduce the burden of HFMD, but a multivalent vaccine should be developed to control the ongoing HFMD epidemic because CV-A6, CV-A10 and CV-A16 were responsible for approximately 12% of severe HFMD cases and cross-reaction between these CV-As and EV-A71 is poor. In order to improve our knowledge of HFMD pathophysiology, I used ECG signal recorded by a wearable device (e-Patch) to depict the distribution of heart rate variability (HRV) indices by severity and by detected pathogens and found that compared to mild disease HRV parameters reflecting parasympathetic nervous system activation in the severe group decreased whereas those mirroring sympathetic activity and autonomic nervous system imbalance increased. In a similar trend, compared to HFMD associated with non-EV-A71, HRV indices reflecting the imbalance between sympathetic and parasympathetic activation in HFMD associated with EV-A71 were significantly higher. This suggests that children with EV-A71 infection were more likely to have ANS imbalance. Alongside with these findings, the feasibility of this wearable device in children has brought promising applications in HFMD case management by early detection of severe disease in future. To inform health policy makers in Vietnam about the burden of HFMD, I also estimated its economic burden. I showed that the total cost per case for mild and severe disease was $245.8 and$1326.7, respectively. Additionally, I also found that compared to CV-A infections, EV-A71 infection resulted in higher illness costs. At nationwide level, the total economic burden in Vietnam was estimated at >US$90 million for two-year period of 2016 – 2017

Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemics

Infectious diseases remain among the top contributors to human illness and death worldwide, among which many diseases produce epidemic waves of infection. The unavailability of specific drugs and ready-to-use vaccines to prevent most of these epidemics makes the situation worse. These force public health officials and policymakers to rely on early warning systems generated by reliable and accurate forecasts of epidemics. Accurate forecasts of epidemics can assist stakeholders in tailoring countermeasures, such as vaccination campaigns, staff scheduling, and resource allocation, to the situation at hand, which could translate to reductions in the impact of a disease. Unfortunately, most of these past epidemics exhibit nonlinear and non-stationary characteristics due to their spreading fluctuations based on seasonal-dependent variability and the nature of these epidemics. We analyse a wide variety of epidemic time series datasets using a maximal overlap discrete wavelet transform (MODWT) based autoregressive neural network and call it EWNet model. MODWT techniques effectively characterize non-stationary behavior and seasonal dependencies in the epidemic time series and improve the nonlinear forecasting scheme of the autoregressive neural network in the proposed ensemble wavelet network framework. From a nonlinear time series viewpoint, we explore the asymptotic stationarity of the proposed EWNet model to show the asymptotic behavior of the associated Markov Chain. We also theoretically investigate the effect of learning stability and the choice of hidden neurons in the proposal. From a practical perspective, we compare our proposed EWNet framework with several statistical, machine learning, and deep learning models. Experimental results show that the proposed EWNet is highly competitive compared to the state-of-the-art epidemic forecasting methods

Development of a Web-enabled Spatial Decision Support System (SDSS) for Prevention of Tick Borne Disease in Kuantan, Malaysia

Ticks are the second most common vectors of human disease after mosquitoes. They are found on many small mammal hosts and also blood-feed on humans with the risk of transmitting diseases. Considering the diseases’ risks, this study has investigated the potential for a web-enabled spatial decision support system (SDSS) to assist government decision-makers in the control, management of resources and prevention of tick borne diseases specifically in the study area of Kuantan, Malaysia

Integrated epidemiological study of Dengue virus transmission in Java, Indonesia

Dengue virus (DENV) is one of the most important arbovirus infections which continues to be spread to many parts of the world. The widespread distribution of the vector Aedes sp, DENV genetic evolution, emergence of a new serotype, global warming, environmental changes, population growth and human mobility are some of the factors affecting DENV transmission. From the many studies conducted on DENV, there is still a lack of integrated research that includes several aspects that affect DENV transmission at a local scale. The aims for this study was to conduct an integrated study of DENV tranmission, covering entomology, DENV, and socio-economic and environmental factors using Banyumas Regency, Java Indonesia, as a model area. The uniqueness of demography, socioeconomy and environment of each area emphasizes the importance of this research. For the entomology factors, this study found that traditional larvae indices such as House Index (HI), Breteau Index (BI) and Container Index (CI), which have been applied for many decades in entomology surveys, are not relevant measurements for determing mosquito populations. These findings supported previous findings that larvae indices cannot predict the transmission risk level and is not correlated with DENV incidence. In this study, adult mosquito collections were found to be a better measurement of risk of DENV transmission. A high vertical transmission rate was also confirmed in an endemic area, which is possibly one explanation for DENV persistence in that area. From a knowledge, awareness and practice (KAP) survey, there is no correlation between knowledge, awareness and practice of DENV prevention and control, and there is also no association between KAP of people with the mosquito infestations in the area of study. This finding leads to the need for better strategies such as education campaigns about DENV prevention to ensure not only an increase in knowledge but also this knowledge translates into practices. During collection of serum samples from DENV infected patients a higher number of adult age groups reported DENV cases, indicating an age group shift from children to adults. Most of the samples (89% ) from positive result of IgG/IgM test had a secondary infection by serological test, which likely increases the possibility of developing severe clinical manisfestations. Many publications believe that secondary infection by different serotypes could cause severe DENV infection. Unfortunately, the serotyping and genotyping of the patient samples could not be completed due to time constraints, so the information of circulating serotypes and genotypes could not be obtained. It would be interesting to further analyse the serotypes and then correlate them with the less or more severe clinical manifestations and also capture the spread of disease from pylogenetic trees from the genotyping results. Based on spatio and spatio-temporal models, it can be concluded that socioeconomic factors, particularly the level of education and the employment structure were the most important risk factors of DENV infection. It was also revealed that enviromental factors had only a little influence on DENV infection, in contrast with many previous beliefs that global warming and environmental changes are the main factors of DENV infection. Human mobility was proposed to be the main explanation of this phenomenon since more educated people and people with good job type tend to have higher exposure to DENV infection due to their movement from home to work places or public areas. This also complements the fact that more adults reported DENV infection during the patient sample collection, suggesting that adult age groups possibly have a higher risk of DENV infection due to higher mobility, which means higher exposure to DENV infection. The possibility of having a secondary infection is also higher in adults since there has been more time to have the first infection and then the second infection. In order to complete this integrated study, the influence of temperature on mosquito immunity, in particular the RNA interference (RNAi) response was tested. Based on RNAi activity in 24°C, 28°C and 32°C, RNAi activity was slightly more efficient following the increase of temperature. In addition, the infection of Aag2 cells with SFV showed that the increasing temperature will result in lower virus replication. We can assume that the lower or higher temperature only contributes a minor effect on RNAi machinery in vitro. In conclusion, this integrated epidemiological study finds that current entomology surveys are not relevant, because they are not associated with the risk of transmission. In addition, socioeconomic factors rather than environmental factors are proposed to be the most significant factor for DENV infection. Findings such as age shift, secondary infection, human mobility and a high vertical transmission rate are important information which could help the public health sector in their planning and action on DENV prevention and control strategies

Influenza Division international activities

In 2010, the Division provided funding support and technical assistance for influenza activities to 48 countries in the form of direct cooperative agreements or indirectly through our partners. Under these agreements, partner countries have made significant progress in the development of their influenza surveillance capacity and pandemic preparedness. Their collective progress is evident in the positive movement of scores captured in 2010 using the Division's National Inventory of Core Capacities for Pandemic Preparedness and Response monitoring and evaluation tool (see page 258). There is no doubt the hard work countries have put in to developing both their laboratory and epidemiologic surveillance systems and strengthening their pandemic preparedness not only enhanced their response to the 2009 influenza pandemic but has also helped to build general capacity for all emerging infectious diseases. In other achievements for 2010, China's National Influenza Center in Beijing was designated a WHO Collaborating Center for Reference and Research on Influenza. The Division has worked closely with the National Influenza Center in Beijing for over two decades and congratulates China on becoming just one of five such Centers globally. Likewise, the Division wishes to congratulate its partner countries who achieved WHO National Influenza Center status in 2010 in the following locations: Guatemala City, Guatemala; Kathmandu, Nepal; Accra, Ghana; Ho Chi Minh City, Vietnam and Vientiane, Lao People's Democratic Republic.Influenza Division international overview -- WHO African Region (AFR) -- WHO Eastern Mediterranean Region (EMR) -- WHO European Region (EUR)...-- WHO Region of the Americas (AMR) -- WHO South-East Asia Region (SEAR) -- WHO Western Pacific Region (WPR) -- influenza research -- Meetings and training -- Influenza Division organization -- ReferencesSpecial thanks to Ann Moen, Emily Cramer, Sarah O'Brien, Howard Hall, Lucinda Johnson and Meg McCarron for editing and producing this 2010 International Influenza Report."Publication date: August 2011."System requirements: Adobe Acrobat Reader.Mode of access: World Wide Web.Includes bibliographical references (p. 292-296).Centers for Disease Control and Prevention. International Influenza Report FY 2010. Atlanta: U.S. Department of Health and Human Services; 2010.Electronic monograph in PDF format (24.29 MB, 304 p.)

Environmental Aspects of Zoonotic Diseases

Environmental Aspects of Zoonotic Diseases provides a definitive description, commentary and research needs of environmental aspects related to zoonotic diseases. There are many interrelated connections between the environment and zoonotic diseases such as: water, soil, air and agriculture. The book presents investigations of these connections, with specific reference to environmental processes such as: deforestation, floods, draughts, irrigation practices, soil transfer and their impact on bacterial, viral, fungal, and parasitological spread. Environmental aspects such as climate (tropical, sub-tropical, temperate, arid and semi-arid), developed and undeveloped countries, animal traffic animal border crossing, commercial animal trade, transportation, as well geography and weather on zoonosis, are also discussed and relevant scientific data is condensed and organized in order to give a better picture of interrelationship between the environment and current spread of zoonotic diseases

Leveraging and adapting global health systems and programs during the COVID-19 pandemic

Overview -- Surveillance, Information, and Laboratory Systems -- Workforce, Institutional, and Public Health Capacity Development -- Clinical and Health Services Delivery and Impact -- Commentaries -- About the Cover.Overview: Partnerships, Collaborations, and Investments Integral to CDC\u2019s International Response to COVID-19 / R. P. Walensky -- Global Responses to the COVID-19 Pandemic / C. H. Cassell et al. -- Surveillance, Information, and Laboratory Systems: Lessons Learned from CDC\u2019s Global COVID-19 Early Warning and Response Surveillance System / P. M. Ricks et al. -- Enhancing Respiratory Disease Surveillance to Detect COVID-19 in Shelters for Displaced Persons, Thailand\u2013Myanmar Border, 2020\u20132021 / B. Knust et al. -- Leveraging International Influenza Surveillance Systems and Programs during the COVID-19 Pandemic / P. Marcenac et al. -- Incorporating COVID-19 into Acute Febrile Illness Surveillance Systems, Belize, Kenya, Ethiopia, Peru, and Liberia, 2020\u20132021 / D. C. Shih et al. -- Extending and Strengthening Routine DHIS2 Surveillance Systems for COVID-19 Responses in Sierra Leone, Sri Lanka, and Uganda / C. Kinkade et al. -- Leveraging PEPFAR-Supported Health Information Systems for COVID-19 Pandemic Response / M. Mirza et al. -- Contribution of PEPFAR-Supported HIV and TB Molecular Diagnostic Networks to COVID-19 Testing Preparedness in 16 Countries / E. Rottinghaus Romano et al. -- A Nationally Representative Survey of COVID-19 in Pakistan, 2021\u20132022 / S. Aheron et al. -- SARS-CoV-2 Prevalence in Malawi Based on Data from Survey of Communities and Health Workers in 5 High-Burden Districts, October 2020 / J. Theu et al. -- Determining Gaps in Publicly Shared SARS-CoV-2 Genomic Surveillance Data by Analysis of Global Submissions / E. C. Ohlsen et al. -- Comparison of COVID-19 Pandemic Waves in 10 Countries in Southern Africa, 2020\u20132021 / J. Smith-Sreen et al. -- Using Population Mobility Patterns to Adapt COVID-19 Response Strategies in 3 East Africa Countries / R. D. Merrill et al. -- Community-Based Surveillance and Geographic Information System\u2012Linked Contact Tracing in COVID-19 Case Identification, Ghana, March\u2012June 2020 / E. Kenu et al. -- The Future of Infodemic Surveillance as Public Health Surveillance / H. Chiou et al. -- Workforce, Institutional, and Public Health Capacity Development: Continuing Contributions of Field Epidemiology Training Programs to Global COVID-19 Response / E. Bell et al. -- India Field Epidemiology Training Program Response to COVID-19 Pandemic, 2020\u20132021 / S. Singh et al. -- COVID-19 Response Roles among CDC International Public Health Emergency Management Fellowship Graduates / S. Krishnan et al. -- Exploratory Literature Review of the Role of National Public Health Institutes in COVID-19 Response / A. Zuber et al. -- Adapting Longstanding Public Health Collaborations between Government of Kenya and CDC Kenya in Response to the COVID-19 Pandemic, 2020\u20132021 / A. Herman-Roloff et al. -- Effect of Nigeria Presidential Task Force on COVID-19 Pandemic, Nigeria / O. Bolu et al. -- Use of Epidemiology Surge Support to Enhance Robustness and Expand Capacity of SARS-CoV-2 Pandemic Response, South Africa / R. Taback-Esra et al. -- Building on Capacity Established through US Centers for Disease Control and Prevention Global Health Programs to Respond to COVID-19, Cameroon / E. Dokubo et al. -- Use of Project ECHO in Response to COVID-19 in Countries Supported by US President\u2019s Emergency Plan for AIDS Relief / J. Wright et al. -- Faith Community Engagement to Mitigate COVID-19 Transmission Associated with Mass Gathering, Uman, Ukraine, September 2021 / L. Erickson-Mamane et al. -- Clinical and Health Services Delivery and Impact: Effects of COVID-19 on Vaccine-Preventable Disease Surveillance Systems in the World Health Organization African Region, 2020 / J. Bigouette et al. -- CDC\u2019s COVID-19 International Vaccine Implementation and Evaluation Program and Lessons from Earlier Vaccine Introductions / H. M. Soeters et al. -- Effects of Decreased Immunization Coverage for Hepatitis B Virus Caused by COVID-19 in World Health Organization Western Pacific and African Regions, 2020 / H. J. Kabore et al. -- Past as Prologue\u2014Use of Rubella Vaccination Program Lessons to Inform COVID-19 Vaccination / M. G. Dixon et al. -- Leveraging Lessons Learned from Yellow Fever and Polio Immunization Campaigns during COVID-19 Pandemic, Ghana, 2021 / K. Amponsa-Achiano et al. -- Effectiveness of Whole-Virus COVID-19 Vaccine among Healthcare Personnel, Lima, Peru / C. S. Arriola et al. -- Leveraging HIV Program and Civil Society to Accelerate COVID-19 Vaccine Uptake, Zambia / P. Bobo et al. -- Adopting World Health Organization Multimodal Infection Prevention and Control Strategies to Respond to COVID-19, Kenya / D. Kimani et al. -- Infection Prevention and Control Initiatives to Prevent Healthcare-Associated Transmission of SARS-CoV-2, East Africa / D. J. Gomes et al. -- Effects of COVID-19 Pandemic on Voluntary Medical Male Circumcision Services for HIV Prevention, Sub-Saharan Africa, 2020 / M. E. Peck et al. -- Sexual Violence Trends before and after Rollout of COVID-19 Mitigation Measures, Kenya / W. Ochieng et al. -- Clinical and Economic Impact of COVID-19 on Agricultural Workers, Guatemala / D. Olson et al. -- Outcomes after Acute Malnutrition Program Adaptations to COVID-19, Uganda, Ethiopia, and Somalia / T. Shragai et al. -- Commentaries: Lessons from Nigeria\u2019s Adaptation of Global Health Initiatives during the COVID-19 Pandemic / C. Ihekweazu -- About the Cover: A United Response to COVID-19\u2014an Artist\u2019s Perspective / B. Breedlove et al

Mental health mobile apps during Covid-19 Pandemic to evaluate stress level in Selangor

The COVID-19 pandemic has impacted negatively on public mental health. As a result, monitoring the level of the population mental health is a priority during crises. This study aims to measure stress during the COVID-19 pandemic in Selangor. Cross-sectional study was done using SELANGKAH apps, where users are Selangor citizens. Data was collected from September 2021 until March 2022. This app was initially used as contact tracing and mental health modules (SEHAT) were added, consisting of a validated Perceived Stress Scale (PSS-10) questionnaire. Out of 42072 SEHAT users, 6411 people had completed the questionnaire. Majority were female (53.6%), Muslims (79.6%), had formal education up to secondary (49.0%), low income (89.9%), and young and middle- aged adults (59.7%). Majority have a moderate stress (66.8%), while 23.3% and 9.9% are low and high levels, respectively. High stress is significantly associated with females, high education, younger age groups, and low monthly income. Several factors could have contributed to this throughout the COVID-19 pandemic, such as online learning, uncertainty on study duration, financial constraints and limited social interactions. Moreover, as an effect of prolonged pandemic and MCO, a surge in the number of job terminations has also affected the source of income, which contributed to high levels of stress among the general population. The level of stress in Selangor was high during the pandemic as an effect of MCO