Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Journal Article · Wed Sep 27 00:00:00 EDT 2023 · Exploration of Digital Health Technologies

DOI:https://doi.org/10.37349/edht.2023.00004· OSTI ID:2224148

Kumar, Praveen ^[1]; Nguyen, Thanh Huong ^[2]; Le, Phong V. V. ^[3]; Yan, Jinhui ^[1]; Zhao, Lei ^[1]; Allan, Brian F. ^[1]; Taylor-Robinson, Andrew W. ^[4]

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1. Univ. of Illinois at Urbana-Champaign, IL (United States)
2. Univ. of Illinois at Urbana-Champaign, IL (United States). Carl R. Woese Institute for Genomic Biology
3. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
4. VinUniversity, Hanoi (Vietnam); Univ. of Pennsylvania, Philadelphia, PA (United States)

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 2224148
• Journal Information: Exploration of Digital Health Technologies, Journal Name: Exploration of Digital Health Technologies Vol. 1; ISSN 2996-9409
• Publisher: Open Exploration
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
Vietnam
arbovirus
climate change
dengue
digital twin
mosquito
urban environment
vector-borne disease