Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection

Olson, Sarah H.; Benedum, Corey M.; Mekaru, Sumiko R.; Preston, Nicholas D.; Mazet, Jonna A. K.; Joly, Damien O.; Brownstein, John S.

doi:10.3201/eid2108.141156

Cited by 46 publications

(59 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

Section: Assisting Governments With Zoonotic Disease Outbreak Investimentioning

confidence: 99%

“…In addition to digital media's value for early event detection, there is also potential for its use as an early warning system through monitoring drivers of disease emergence (Olson et al, 2015). The consortium developed a scientific framework for a digital disease driver surveillance platform (Olson et al, 2015). The platform has the potential to identify locations and periods of time with elevated infectious disease risk with alerting of public health officials to the need for active surveillance and intervention prior to pathogen spillover events.…”

Section: Assisting Governments With Zoonotic Disease Outbreak Investimentioning

confidence: 99%

See 1 more Smart Citation

One Health proof of concept: Bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface

Kelly

Karesh

Johnson

et al. 2017

Preventive Veterinary Medicine

Self Cite

143

117

View full text Add to dashboard Cite

As the world continues to react and respond inefficiently to emerging infectious diseases, such as Middle Eastern Respiratory Syndrome and the Ebola and Zika viruses, a growing transdisciplinary community has called for a more proactive and holistic approach to prevention and preparedness - One Health. Such an approach presents important opportunities to reduce the impact of disease emergence events and also to mitigate future emergence through improved cross-sectoral coordination. In an attempt to provide proof of concept of the utility of the One Health approach, the US Agency for International Development's PREDICT project consortium designed and implemented a targeted, risk-based surveillance strategy based not on humans as sentinels of disease but on detecting viruses early, at their source, where intervention strategies can be implemented before there is opportunity for spillover and spread in people or food animals. Here, we share One Health approaches used by consortium members to illustrate the potential for successful One Health outcomes that can be achieved through collaborative, transdisciplinary partnerships. PREDICT's collaboration with partners around the world on strengthening local capacity to detect hundreds of viruses in wild animals, coupled with a series of cutting-edge virological and analytical activities, have significantly improved our baseline knowledge on the zoonotic pool of viruses and the risk of exposure to people. Further testament to the success of the project's One Health approach and the work of its team of dedicated One Health professionals are the resulting 90 peer-reviewed, scientific publications in under 5 years that improve our understanding of zoonoses and the factors influencing their emergence. The findings are assisting in global health improvements, including surveillance science, diagnostic technologies, understanding of viral evolution, and ecological driver identification. Through its One Health leadership and multi-disciplinary partnerships, PREDICT has forged new networks of professionals from the human, animal, and environmental health sectors to promote global health, improving our understanding of viral disease spillover from wildlife and implementing strategies for preventing and controlling emerging disease threats.

show abstract

Section: Assisting Governments With Zoonotic Disease Outbreak Investimentioning

confidence: 99%

Section: Assisting Governments With Zoonotic Disease Outbreak Investimentioning

confidence: 99%

One Health proof of concept: Bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface

Kelly

Karesh

Johnson

et al. 2017

Preventive Veterinary Medicine

Self Cite

143

117

View full text Add to dashboard Cite

show abstract

“…Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and incidence of the disease [2,3,4]. Early detection of disease activity and rapid responses can reduce the impact of diseases [5].…”

Section: Introductionmentioning

confidence: 99%

Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level

et al. 2017

View full text Add to dashboard Cite

BackgroundInfectious diseases are a leading threat to public health. Accurate and timely monitoring of disease risk and progress can reduce their impact. Mentioning a disease in social networks is correlated with physician visits by patients, and can be used to estimate disease activity. Dengue is the fastest growing mosquito-borne viral disease, with an estimated annual incidence of 390 million infections, of which 96 million manifest clinically. Dengue burden is likely to increase in the future owing to trends toward increased urbanization, scarce water supplies and, possibly, environmental change. The epidemiological dynamic of Dengue is complex and difficult to predict, partly due to costly and slow surveillance systems.Methodology / Principal findingsIn this study, we aimed to quantitatively assess the usefulness of data acquired by Twitter for the early detection and monitoring of Dengue epidemics, both at country and city level at a weekly basis. Here, we evaluated and demonstrated the potential of tweets modeling for Dengue estimation and forecast, in comparison with other available web-based data, Google Trends and Wikipedia access logs. Also, we studied the factors that might influence the goodness-of-fit of the model. We built a simple model based on tweets that was able to ‘nowcast’, i.e. estimate disease numbers in the same week, but also ‘forecast’ disease in future weeks. At the country level, tweets are strongly associated with Dengue cases, and can estimate present and future Dengue cases until 8 weeks in advance. At city level, tweets are also useful for estimating Dengue activity. Our model can be applied successfully to small and less developed cities, suggesting a robust construction, even though it may be influenced by the incidence of the disease, the activity of Twitter locally, and social factors, including human development index and internet access.ConclusionsTweets association with Dengue cases is valuable to assist traditional Dengue surveillance at real-time and low-cost. Tweets are able to successfully nowcast, i.e. estimate Dengue in the present week, but also forecast, i.e. predict Dengue at until 8 weeks in the future, both at country and city level with high estimation capacity.

show abstract

“…About 75% of emerging diseases are zoonotic, meaning that they can be naturally transmitted from vertebrate animals to humans and vice versa [5]. These diseases emerge due to factors such as ecosystem change, industrial development, social inequalities, and climate change that are linked to human population growth [6][7][8]. Several sectors, ministries, and disciplines must, therefore, collaborate to prevent and control these diseases and to achieve optimal health for people, animals, and the ecosystem [9].…”

Section: Introductionmentioning

confidence: 99%

Organizational leadership perspectives in implementation of the One Health approach: A case of the Zoonotic Disease Unit and core One Health implementers in Kenya

Nyariki¹,

Muturi²,

Mwatondo³

et al. 2017

Int J One Health

View full text Add to dashboard Cite

Aim: This study examined organizational leadership as a cross-sectoral collaboration factor in the implementation of the One Health (OH) approach using Kenya's Zoonotic Disease Unit and its core OH implementers as an example. Materials and Method:The study used a mixed methods research design. A semi-structured questionnaire was administered to 71 respondents, and key informants were interviewed using an interview guide. All the seven key informants and 53 (74%) of the respondents participated in the study. Data were checked for consistency, coded, entered into the Statistical Package for the Social Sciences, and analyzed using descriptive and correlational statistics. Interview data were transcribed and analyzed thematically.Results: From the analysis, 41/53 (77.2%) of the respondents were senior personnel, 51/53 (85%) of them had worked for 5 years and above in their organizations, and 38/53 (71.7%) had at least a Master's degree. The study established that although most leaders in the organizations had embraced the OH approach, they were not actively involved in its implementation due to constraints such as inadequate funding. There were moderate and statistically significant positive correlations between participation in leadership roles in implementing the OH approach and the level of awareness (Rs (51)=0.54, p<0.001) as well as level of sensitization (Rs (51)=0.52, p<0.001). Majority (86%) of respondents acknowledged that top government leaders were not well sensitized about the OH approach. Conclusion:Organizational leadership plays an important role in the implementation of the OH approach. However, sensitization of leaders about the OH approach needs to be enhanced and expanded.

show abstract

Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection

Abstract: Improved and expanded data collection is required to fulfil the promise of an early-warning digital system.

Cited by 46 publications

References 26 publications

One Health proof of concept: Bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface

One Health proof of concept: Bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface

Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level

Organizational leadership perspectives in implementation of the One Health approach: A case of the Zoonotic Disease Unit and core One Health implementers in Kenya

Contact Info

Product

Resources

About