Spatio-Temporal Patterns of Dengue Fever in Cali, Colombia

2013 ◽  
Vol 4 (4) ◽  
pp. 58-75 ◽  
Author(s):  
Eric Delmelle ◽  
Irene Casas ◽  
Jorge H. Rojas ◽  
Alejandro Varela
Keyword(s):  
Dengue Fever ◽  
Control Strategies ◽  
Effective Means ◽  
Virus Transmission ◽  
Deep Understanding ◽  
Space Time ◽  
Effective Vaccine ◽  
Analysis Tool ◽  
K Function ◽  
Spatio Temporal

Dengue fever is an arboviral disease typical of the tropics that can be life-threatening and if not controlled properly may result in an epidemic. The absence of an effective vaccine makes strategies to prevent the virus transmission the most effective means of control. The planning of such strategies, however, is difficult due to the constant movement of individuals and mosquito host (Aedes aegypti). In this paper, the spatial and temporal relations that might exist between infected individuals during a dengue-epidemic year are explored. This research is motivated in that a deep understanding of potential transmission patterns between individuals might lead to a better design and planning of control strategies. A GIS-based Health Exploratory AnaLysis Tool (HELP) is used to compute space-time relationships by means of spatial K-function, kernel density, space-time K-function and linking pairs of cases within significant time and space intervals. Significant clustering was observed at a scale of 50 meters and 750 meters, respectively while temporal significance was determined at two days and five to eight days. While an increase of cases occurs in the months following severe droughts due to an El Niño phenomenon, the location of clusters remains relatively stable. These are observed near areas where potential habitats for the mosquito exist such as storm drains, hard surfaces where water accumulates (e.g., vases, containers), but also in poorer neighborhoods. The results from the spatial analysis provide valuable information for health care managers to take preventive actions at the municipality level.

scholarly journals Multivariate spatio-temporal analysis of the global COVID-19 pandemic

2021 ◽  
Author(s):  
Wen Xiang ◽  
Ben Swallow
Keyword(s):  
Control Strategies ◽  
Temporal Structure ◽  
Temporal Trends ◽  
Virus Transmission ◽  
Temporal Analysis ◽  
Global Scale ◽  
Global Dynamics ◽  
Multivariate Statistical ◽  
Wide Range ◽  
Spatio Temporal

AbstractThe COVID-19 pandemic has caused significant mortality and disruption on a global scale not seen in living memory. Understanding the spatial and temporal vectors of transmission as well as similarities in the trajectories of recorded cases and deaths across countries can aid in understanding the benefit or otherwise of varying interventions and control strategies on virus transmission. It can also highlight emerging globa trends as they occur. Data on number of cases and deaths across the globe have been made available through a variety of databases and provide a wide range of opportunities for the application of multivariate statistical methods to extract information on similarity or difference from them. Here we conduct spatial and temporal multivariate statistical analyses of global COVID-19 cases and deaths for the period spanning January to August 2020, using a variety of distance based multivariate methods to cluster countries according to similar temporal trends in cases and deaths resulting from COVID-19. We also use novel air passenger data as a proxy for movement between countries. The air passenger movement can act as an important vector of transmission and thus scaling covariance matrices before conducting dimension reduction techniques can account for known structures in the data and help highlight important residual spatial and/or temporal trends that may then be attributable to the success of interventions or other cultural differences. Global temporal structure is found to be of significantly more importance than local spatial structure in terms of global dynamics. Our results highlight a significant global change in case and mortality daynamics from early-August, consistent in timing with the emergence of new strains with highger levels of transmission. We propose the methodology offers great potential in real-time analysis of complex, noisy spatio-temporal data and the extraction of emerging changes in pandemic dynamics that can support policy and decision makers.

scholarly journals Spatio-Temporal Patterns of Dengue Incidence in Medan City, North Sumatera, Indonesia

2021 ◽  
Vol 6 (1) ◽  
pp. 30
Author(s):  
Ayodhia Pitaloka Pasaribu ◽  
Tsheten Tsheten ◽  
Muhammad Yamin ◽  
Yulia Maryani ◽  
Fahmi Fahmi ◽  
...  
Keyword(s):  
Control Strategies ◽  
Public Health Problem ◽  
Temporal Patterns ◽  
Space Time ◽  
Scan Statistic ◽  
Cold Spots ◽  
Spatio Temporal ◽  
Dengue Control ◽  
And Control ◽  
Time Scan

Dengue has been a perennial public health problem in Medan city, North Sumatera, despite the widespread implementation of dengue control. Understanding the spatial and temporal pattern of dengue is critical for effective implementation of dengue control strategies. This study aimed to characterize the epidemiology and spatio-temporal patterns of dengue in Medan City, Indonesia. Data on dengue incidence were obtained from January 2016 to December 2019. Kulldorff’s space-time scan statistic was used to identify dengue clusters. The Getis-Ord Gi* and Anselin Local Moran’s I statistics were used for further characterisation of dengue hotspots and cold spots. Results: A total of 5556 cases were reported from 151 villages across 21 districts in Medan City. Annual incidence in villages varied from zero to 439.32 per 100,000 inhabitants. According to Kulldorf’s space-time scan statistic, the most likely cluster was located in 27 villages in the south-west of Medan between January 2016 and February 2017, with a relative risk (RR) of 2.47. Getis-Ord Gi* and LISA statistics also identified these villages as hotpot areas. Significant space-time dengue clusters were identified during the study period. These clusters could be prioritized for resource allocation for more efficient prevention and control of dengue.

scholarly journals Pupal cannibalism by worker honey bees contributes to the spread of deformed wing virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francisco Posada-Florez ◽  
Zachary S. Lamas ◽  
David J. Hawthorne ◽  
Yanping Chen ◽  
Jay D. Evans ◽  
...  
Keyword(s):  
Honey Bees ◽  
Control Strategies ◽  
Virus Transmission ◽  
Experimental Conditions ◽  
Colony Losses ◽  
Viral Pathogen ◽  
Deformed Wing Virus ◽  
Hygienic Behaviour ◽  
Pathogen Virulence ◽  
Comprehensive Knowledge

AbstractTransmission routes impact pathogen virulence and genetics, therefore comprehensive knowledge of these routes and their contribution to pathogen circulation is essential for understanding host–pathogen interactions and designing control strategies. Deformed wing virus (DWV), a principal viral pathogen of honey bees associated with increased honey bee mortality and colony losses, became highly virulent with the spread of its vector, the ectoparasitic mite Varroa destructor. Reproduction of Varroa mites occurs in capped brood cells and mite-infested pupae from these cells usually have high levels of DWV. The removal of mite-infested pupae by worker bees, Varroa Sensitive Hygiene (VSH), leads to cannibalization of pupae with high DWV loads, thereby offering an alternative route for virus transmission. We used genetically tagged DWV to investigate virus transmission to and between worker bees following pupal cannibalisation under experimental conditions. We demonstrated that cannibalization of DWV-infected pupae resulted in high levels of this virus in worker bees and that the acquired virus was then transmitted between bees via trophallaxis, allowing circulation of Varroa-vectored DWV variants without the mites. Despite the known benefits of hygienic behaviour, it is possible that higher levels of VSH activity may result in increased transmission of DWV via cannibalism and trophallaxis.

scholarly journals Yellow Fever Outbreak in Eastern Senegal, 2020–2021

Viruses ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1475
Author(s):  
Moussa Moïse Diagne ◽  
Marie Henriette Dior Ndione ◽  
Alioune Gaye ◽  
Mamadou Aliou Barry ◽  
Diawo Diallo ◽  
...  
Keyword(s):  
Yellow Fever ◽  
Yellow Fever Virus ◽  
Mosquito Species ◽  
Virus Transmission ◽  
Genomic Analysis ◽  
Hemorrhagic Fever ◽  
Fever Virus ◽  
World Health ◽  
Effective Vaccine ◽  
Ministry Of Health

Yellow fever virus remains a major threat in low resource countries in South America and Africa despite the existence of an effective vaccine. In Senegal and particularly in the eastern part of the country, periodic sylvatic circulation has been demonstrated with varying degrees of impact on populations in perpetual renewal. We report an outbreak that occurred from October 2020 to February 2021 in eastern Senegal, notified and managed through the synergistic effort yellow fever national surveillance implemented by the Senegalese Ministry of Health in collaboration with the World Health Organization, the countrywide 4S network set up by the Ministry of Health, the Institut Pasteur de Dakar, and the surveillance of arboviruses and hemorrhagic fever viruses in human and vector populations implemented since mid 2020 in eastern Senegal. Virological analyses highlighted the implication of sylvatic mosquito species in virus transmission. Genomic analysis showed a close relationship between the circulating strain in eastern Senegal, 2020, and another one from the West African lineage previously detected and sequenced two years ago from an unvaccinated Dutch traveler who visited the Gambia and Senegal before developing signs after returning to Europe. Moreover, genome analysis identified a 6-nucleotide deletion in the variable domain of the 3′UTR with potential impact on the biology of the viral strain that merits further investigations. Integrated surveillance of yellow fever virus but also of other arboviruses of public health interest is crucial in an ecosystem such as eastern Senegal.

Study of the Spatio-Temporal Data Model in Sea Battlefield

2012 ◽  
Vol 246-247 ◽  
pp. 744-748
Author(s):  
Yue Lin Sun ◽  
Lei Bao ◽  
Yi Hang Peng
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Space Time ◽  
Comprehensive Analysis ◽  
Temporal Data ◽  
Data Types ◽  
Spatio Temporal ◽  
The Right ◽  
Effective Analysis

An effective analysis of the battlefield situation and spatio-temporal data model in a sea battlefield has great significance for the commander to perceive the battlefield situation and to make the right decisions. Based on the existing spatio-temporal data model, the present paper gives a comprehensive analysis of the characteristics of sea battlefield data, and chooses the object-oriented spatio-temporal data model to modify it; at the same time this paper introduces sea battlefield space-time algebra system to define various data types formally, which lays the foundation for the establishment of the sea battlefield spatio-temporal data model.

scholarly journals Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review

2018 ◽  
Vol 147 ◽  
Author(s):  
A. Aswi ◽  
S. M. Cramb ◽  
P. Moraga ◽  
K. Mengersen
Keyword(s):  
Dengue Fever ◽  
Random Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Assessment Tool ◽  
Temporal Dynamics ◽  
Random Effect ◽  
Temperature And Precipitation ◽  
Generalised Linear Mixed Model ◽  
Spatio Temporal

AbstractDengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.

scholarly journals SPACE-TIME TRANSFORMATIONS IN THE UPPER XINGU AND UPPER RIO NEGRO

2015 ◽  
Vol 5 (3) ◽  
pp. 699-724
Author(s):  
Geraldo Andrello ◽  
Antonio Guerreiro ◽  
Stephen Hugh-Jones
Keyword(s):  
Social Organization ◽  
Social Life ◽  
Space Time ◽  
Unequal Distribution ◽  
Rio Negro ◽  
The People ◽  
The Social ◽  
Esoteric Knowledge ◽  
Spatio Temporal ◽  
Time Transformations

Abstract The multi-ethnic and multilingual complexes of the Upper Rio Negro and the Upper Xingu share common aspects that frequently emerge in ethnographies, including notions of descent, hierarchical social organization and ritual activities, as well as a preference for forms of exogamy and the unequal distribution of productive and ritual specialties and esoteric knowledge. In this article we investigate how the people of both regions conceive of their humanity and that of their neighbours as variations on a shared form, since in both regions ritual processes for negotiating positions and prerogatives seems to take the place of the latent state of warfare typical of the social life of other Amazonian peoples. In this article we will synthesize, for each region, the spatio-temporal processes that underscore the eminently variable constitution of collectivities, seeking, in conclusion, to isolate those elements that the two regions have in common.

scholarly journals Exploiting vulnerabilities in cancer signalling networks to combat targeted therapy resistance

2018 ◽  
Vol 62 (4) ◽  
pp. 583-593 ◽  
Author(s):  
Peter T. Harrison ◽  
Paul H. Huang
Keyword(s):  
Drug Resistance ◽  
Targeted Therapy ◽  
Kinase Inhibitors ◽  
Effective Means ◽  
Deep Understanding ◽  
Therapy Resistance ◽  
Resistance Mechanisms ◽  
Precision Oncology ◽  
First Line ◽  
Clinical Responses

Drug resistance remains one of the greatest challenges facing precision oncology today. Despite the vast array of resistance mechanisms that cancer cells employ to subvert the effects of targeted therapy, a deep understanding of cancer signalling networks has led to the development of novel strategies to tackle resistance both in the first-line and salvage therapy settings. In this review, we provide a brief overview of the major classes of resistance mechanisms to targeted therapy, including signalling reprogramming and tumour evolution; our discussion also focuses on the use of different forms of polytherapies (such as inhibitor combinations, multi-target kinase inhibitors and HSP90 inhibitors) as a means of combating resistance. The promise and challenges facing each of these polytherapies are elaborated with a perspective on how to effectively deploy such therapies in patients. We highlight efforts to harness computational approaches to predict effective polytherapies and the emerging view that exceptional responders may hold the key to better understanding drug resistance. This review underscores the importance of polytherapies as an effective means of targeting resistance signalling networks and achieving durable clinical responses in the era of personalised cancer medicine.

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