scholarly journals A model for the spatial transmission of dengue with daily movement between villages and a city

2013 ◽  
Vol 31 (2) ◽  
pp. 150-178 ◽  
Author(s):  
A. L. Nevai ◽  
E. Soewono
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei Liu ◽  
Dongming Wang ◽  
Shuiqiong Hua ◽  
Cong Xie ◽  
Bin Wang ◽  
...  

AbstractFew study has revealed spatial transmission characteristics of COVID-19 in Wuhan, China. We aimed to analyze the spatiotemporal spread of COVID-19 in Wuhan and its influence factors. Information of 32,682 COVID-19 cases reported through March 18 were extracted from the national infectious disease surveillance system. Geographic information system methods were applied to analysis transmission of COVID-19 and its influence factors in different periods. We found decrease in effective reproduction number (Rt) and COVID-19 related indicators through taking a series of effective public health measures including restricting traffic, centralized quarantine and strict stay-at home policy. The distribution of COVID-19 cases number in Wuhan showed obvious global aggregation and local aggregation. In addition, the analysis at streets-level suggested population density and the number of hospitals were associated with COVID-19 cases number. The epidemic situation showed obvious global and local spatial aggregations. High population density with larger number of hospitals may account for the aggregations. The epidemic in Wuhan was under control in a short time after strong quarantine measures and restrictions on movement of residents were implanted.


2021 ◽  
Author(s):  
Marie‐Pier Poulin ◽  
Jeanne Clermont ◽  
Dominique Berteaux

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jay A. VonBank ◽  
Mitch D. Weegman ◽  
Paul T. Link ◽  
Stephanie A. Cunningham ◽  
Kevin J. Kraai ◽  
...  

Abstract Background Animal movement patterns are the result of both environmental and physiological effects, and the rates of movement and energy expenditure of given movement strategies are influenced by the physical environment an animal inhabits. Greater white-fronted geese in North America winter in ecologically distinct regions and have undergone a large-scale shift in wintering distribution over the past 20 years. White-fronts continue to winter in historical wintering areas in addition to contemporary areas, but the rates of movement among regions, and energetic consequences of those decisions, are unknown. Additionally, linkages between wintering and breeding regions are generally unknown, and may influence within-winter movement rates. Methods We used Global Positioning System and acceleration data from 97 white-fronts during two winters to elucidate movement characteristics, model regional transition probabilities using a multistate model in a Bayesian framework, estimate regional energy expenditure, and determine behavior time-allocation influences on energy expenditure using overall dynamic body acceleration and linear mixed-effects models. We assess the linkages between wintering and breeding regions by evaluating the winter distributions for each breeding region. Results White-fronts exhibited greater daily movement early in the winter period, and decreased movements as winter progressed. Transition probabilities were greatest towards contemporary winter regions and away from historical wintering regions. Energy expenditure was up to 55% greater, and white-fronts spent more time feeding and flying, in contemporary wintering regions compared to historical regions. White-fronts subsequently summered across their entire previously known breeding distribution, indicating substantial mixing of individuals of varying breeding provenance during winter. Conclusions White-fronts revealed extreme plasticity in their wintering strategy, including high immigration probability to contemporary wintering regions, high emigration from historical wintering regions, and high regional fidelity to western regions, but frequent movements among eastern regions. Given that movements of white-fronts trended toward contemporary wintering regions, we anticipate that a wintering distribution shift eastward will continue. Unexpectedly, greater energy expenditure in contemporary wintering regions revealed variable energetic consequences of choice in wintering region and shifting distribution. Because geese spent more time feeding in contemporary regions than historical regions, increased energy expenditure is likely balanced by increased energy acquisition in contemporary wintering areas.


2021 ◽  
Vol 10 (8) ◽  
pp. 517
Author(s):  
Patricia K. Doyle-Baker ◽  
Andrew Ladle ◽  
Angela Rout ◽  
Paul Galpern

For many university students, commuting to and from campus constitutes a large proportion of their daily movement, and therefore it may influence their ability and willingness to spend time on campus or to participate in campus activities. To assess student engagement on campus, we collected smartphone GPS location histories from volunteers (n = 280) attending university in a major Canadian city. We investigated how campus visit length and frequency were related to characteristics of the commute using Bayesian regression models. Slower commutes and commutes over longer distances were associated with more time spent but less frequent visits to campus. Our results demonstrate that exposure to campus life, and therefore the potential for student engagement, may relate not just to whether a student lives on or near campus, but also to urban environmental factors that interact to influence the commuting experience.


Computation ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 30
Author(s):  
Jeerawan Suksamran ◽  
Yongwimon Lenbury ◽  
Sanoe Koonprasert

Porcine reproductive and respiratory syndrome virus (PRRSV) causes reproductive failure in sows and respiratory disease in piglets and growing pigs. The disease rapidly spreads in swine populations, making it a serious problem causing great financial losses to the swine industry. However, past mathematical models used to describe the spread of the disease have not yielded sufficient understanding of its spatial transmission. This work has been designed to investigate a mathematical model for the spread of PRRSV considering both time and spatial dimensions as well as the observed decline in infectiousness as time progresses. Moreover, our model incorporates into the dynamics the assumption that some members of the infected population may recover from the disease and become immune. Analytical solutions are derived by using the modified extended hyperbolic tangent method with the introduction of traveling wave coordinate. We also carry out a stability and phase analysis in order to obtain a clearer understanding of how PRRSV spreads spatially through time.


Author(s):  
Manasa S. Yerramalla ◽  
Duncan E. McGregor ◽  
Vincent T. van Hees ◽  
Aurore Fayosse ◽  
Aline Dugravot ◽  
...  

Abstract Background Moderate-to-vigorous physical activity (MVPA) is proposed as key for cardiovascular diseases (CVD) prevention. At older ages, the role of sedentary behaviour (SB) and light intensity physical activity (LIPA) remains unclear. Evidence so far is based on studies examining movement behaviours as independent entities ignoring their co-dependency. This study examines the association between daily composition of objectively-assessed movement behaviours (MVPA, LIPA, SB) and incident CVD in older adults. Methods Whitehall II accelerometer sub-study participants free of CVD at baseline (N = 3319, 26.7% women, mean age = 68.9 years in 2012–2013) wore a wrist-accelerometer from which times in SB, LIPA, and MVPA during waking period were extracted over 7 days. Compositional Cox regression was used to estimate the hazard ratio (HR) for incident CVD for daily compositions of movement behaviours characterized by 10 (20 or 30) minutes greater duration in one movement behaviour accompanied by decrease in another behaviour, while keeping the third behaviour constant, compared to reference composition. Analyses were adjusted for sociodemographic, lifestyle, cardiometabolic risk factors and multimorbidity index. Results Of the 3319 participants, 299 had an incident CVD over a mean (SD) follow-up of 6.2 (1.3) years. Compared to daily movement behaviour composition with MVPA at recommended 21 min per day (150 min/week), composition with additional 10 min of MVPA and 10 min less SB was associated with smaller risk reduction – 8% (HR, 0.92; 95% CI, 0.87–0.99) – than the 14% increase in risk associated with a composition of similarly reduced time in MVPA and more time in SB (HR, 1.14; 95% CI, 1.02–1.27). For a given MVPA duration, the CVD risk did not differ as a function of LIPA and SB durations. Conclusions Among older adults, an increase in MVPA duration at the expense of time in either SB or LIPA was found associated with lower incidence of CVD. This study lends support to public health guidelines encouraging increase in MVPA or at least maintain MVPA at current duration.


Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 177-191
Author(s):  
Theodoros Anagnostopoulos

Smart Cities (or Cities 2.0) are an evolution in citizen habitation. In such cities, transport commuting is changing rapidly with the proliferation of contemporary vehicular technology. New models of vehicle ride sharing systems are changing the way citizens commute in their daily movement schedule. The use of a private vehicle per single passenger transportation is no longer viable in sustainable Smart Cities (SC) because of the vehicles’ resource allocation and urban pollution. The current research on car ride sharing systems is widely expanding in a range of contemporary technologies, however, without covering a multidisciplinary approach. In this paper, the focus is on performing a multidisciplinary research on car riding systems taking into consideration personalized user mobility behavior by providing next destination prediction as well as a recommender system based on riders’ personalized information. Specifically, it proposes a predictive vehicle ride sharing system for commuting, which has impact on the SC green ecosystem. The adopted system also provides a recommendation to citizens to select the persons they would like to commute with. An Artificial Intelligence (AI)-enabled weighted pattern matching model is used to assess user movement behavior in SC and provide the best predicted recommendation list of commuting users. Citizens are then able to engage a current trip to next destination with the more suitable user provided by the list. An experimented is conducted with real data from the municipality of New Philadelphia, in SC of Athens, Greece, to implement the proposed system and observe certain user movement behavior. The results are promising for the incorporation of the adopted system to other SCs.


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