Prediction of dengue outbreaks in Mexico based on entomological, meteorological and demographic data

Sánchez‐González, Gilberto; Condé, Renaud; Moreno, Raúl Noguez; Vázquez, Pablo Carlos López

doi:10.1371/journal.pone.0196047

Cited by 22 publications

(21 citation statements)

References 28 publications

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“…2.2 Population density in village factor (PDVF) indicates the number of people per square kilometre. This model of human population density predicted dengue outbreak 8 , 26 because dengue virus transmission occurs between humans and mosquitoes. High population density is associated with increasing dengue incidence.…”

Section: Resultsmentioning

confidence: 99%

“…Among them, 1.8 billion live in South-East Asia and Western Pacific regions, and 500 000 dengue cases require hospitalization yearly, with a death rate of 2.5%. 1 - 3 The main risk factors of dengue include rainfall, temperature, 4 , 5 mosquito density, 6 density of people, 7 , 8 dengue types, 5 non-specific treatment, 1 , 2 no effective dengue vaccine, 5 , 9 ineffective drugs, 5 human immunity, 10 people’s movement across areas, 11 , 12 population density, 13 attitude toward dengue prevention, 14 , 15 and occupation. 12 Interventions to address dengue problems combine community mobilization, entomological methods, and chemical and biological controls.…”

Section: Introductionmentioning

confidence: 99%

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Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Suwanbamrung

Kaewsawat

et al. 2021

J Prim Care Community Health

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Background: Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation. Methods: This participatory research conducted in Southern Thailand included the following 5 phases: (i) preparing communities in 3 districts; (ii) developing risk dengue village prediction criteria; (iii) applying computer program; (iv) predicting village dengue risk with 75 public health providers in 39 PCUs; and (v) utilizing findings to strengthen dengue prevention activities in 220 villages. Data collecting for prediction used secondary data from primary care units in the past 5 year and current year. Descriptive statistics used calculating criteria and comparing with standard level to adjust score of risk. Results: Risk dengue village assessment criteria had 2 aspects: dengue severity (3 factors) and dengue outbreak opportunity (3 factors). Total scores were 33 points and cut-off of 17 points for high and low dengue risks villages. All criteria were applied using computer program ( http://surat.denguelim.com ). Risk prediction involved stakeholder participation in 220 villages, and used for strengthening dengue prevention activities. The concept of integrated vector management included larval indices surveillance system, garbage management, larval indices level lower than the standard, community capacity activities for dengue prevention, and school-based dengue prevention. The risk prediction criteria and process mobilized villages for dengue prevention activities to decrease morbidity rate. Conclusion: Dengue risk assessment criteria were appropriated within the village, with its smallest unit, the household, included. The data can be utilized at village levels for evaluating dengue outbreak risks.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Suwanbamrung

Kaewsawat

et al. 2021

J Prim Care Community Health

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“…require optimum temperatures ranging between 15–35 °C to fully develop and survive. Moreover, studies by Chen & Hsieh [52] in Taiwan and Sánchez-González et al [53] in Mexico indicated that the highest risk of dengue transmission generally occurs at a temperature of 28 °C. There is compelling evidence that this optimal temperature reduced gonotrophic cycles for Aedes mosquitoes, prolonging of the mosquitoes’ life expectancy, shortening of the extrinsic incubation periods of arboviruses, and facilitating the dispersal of vectors across broader geographical areas [13, 14, 51], which could potentially lead to a greater probability of dengue transmission.…”

Section: Discussionmentioning

confidence: 99%

Paediatric dengue infection in Cirebon, Indonesia: a temporal and spatial analysis of notified dengue incidence to inform surveillance

et al. 2019

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Background The recent situation of dengue infection in Cirebon district is concerning due to an upsurge trend since the year 2010. The largest dengue outbreak was reported in 2016 which has affected more than 1600 children. A study was conducted to explore the temporal variability of dengue outbreak in Cirebon’s child population in during 2011–2017, and to assess the short-term effects of climatic and environmental factor on dengue incidence. In addition, the spatial pattern of dengue incidence in children and high-risk villages were investigated. Methods A total of 4597 confirmed dengue cases in children notified from January 2011 to December 2017 were analysed. Seasonal decomposition analysis was carried out to examine the annual seasonality. A generalized linear model (GLM) was applied to assess the short-term effect of climate and normalized difference vegetation index (NDVI) on dengue incidence. The incidence rate ratio (IRR) of the final model was reported. Spatial analyses were conducted by using Moran’s I and local indicator of spatial association (LISA) analyses to explore geographical clustering in incidence and to identify high-risk villages for dengue, respectively. Results An annual dengue epidemic period was observed with peaks occurring every January/February. Based on the GLM, temperature at a lag 4 months (IRR = 1.27; 95% confidence interval, 95% CI: 1.22–1.31, P < 0.001), rainfall at a lag 2 months (IRR = 0.99, 95% CI: 0.99–0.99, P < 0.001), humidity at lag 0 month (IRR = 1.05, 95% CI: 1.04–1.06, P < 0.001) and NDVI at a lag 1 month (IRR = 3.07, 95% CI: 1.94–4.86, P < 0.001) were associated with dengue incidence in children. The dengue incidence in children was spatially varied and clustered at the village level across Cirebon. During 2011–2017, a total of 38 high-risk villages for dengue were identified, which were mainly located in the northern part of Cirebon. Conclusions Seasonal patterns of dengue incidence in children in Cirebon were strongly associated with rainfall, temperature, humidity and NDVI variability, suggesting that climatic and environmental data could be used to help predict dengue outbreaks. Our spatial analysis revealed a clustered pattern in dengue incidence and high-risk villages for dengue across Cirebon, suggesting that effective interventions such as vector surveillance and school-based campaigns should be prioritized around the identified high-risk villages. Temporal and spatial analytical tools could be utilized to support local health authorities to apply timely and targeted public health interventions and help better planning and decision-making in order to minimize the impact of dengue outbreaks. Electronic supplementary material The online version of this article (10.1186/s13071-019-3446-3) contains s...

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“…The same occurs with the number of infection recoveries, the TNSEs and the NSCEs. The rain season is modeled as a 4-month period sine function, were the temperature changes from 25 °C to 30 °C, which cross the optimal transmission temperature ranging between 27-28 °C, as we already showed in our previous work (23). The parameters used to calculate the model are show at Table 1.…”

Section: Methodsmentioning

confidence: 94%

New Genotype Emergence of DENV are Constrained by the Double Host Selection, Reducing the Probability of Alternative Serotype Emergence

Sánchez‐González

Condé

2019

Preprint

Self Cite

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25 Since their discovery and sequencing 40 years ago, the DENV genotypes have shown an extreme 26 coherence regarding the serotype class they code for. Considering the RNA virus mutation rate, 27 we used Timed Markov Model to explore the transmission possibilities of mutated viruses and the 28 statistical eventualities of new serotype emergence. We find that around 1 000 years are required 29 for a new serotype to emerge, in line with phylogenetic analysis of the Dengue serotypes. Our 30 work provides a mechanistic explanation of the strictness and low probability of a new Dengue 31 virus serotype occurrence. 32 33 Author summary 34 Recent Dengue virus global spread has drawn the attention of the Public Health Policy makers in 35 developing countries and developed countries as well. The infection gravity and the hemorrhagic 36 dengue syndromes have been related with the absence or presence of previous DENV immunity.37 Therefore, the emergence of a new DENV serotype and its spread constitute a matter of concern.38 Here, we constructed a mathematical model to determine the probability of such event, as well as 39 de-entangle the mechanistic reasons behind the low serotype emergence factor of the DENV. 40 41 Introduction 42 Dengue virus infection have showed a marked increase during the last two decades, imposing a 43 sizable burden on the health system and economy of the affected Latin-American countries (1). 44 Vaccine prospects have shown limited infection protection efficacy (42.3% to 77.7% of protection, 45 in function of the serotype), though drastically decreasing the appearance of hemorrhagic 46 symptoms in the infected population (2). 47 48 Part of the difficulty for Dengue vaccine design arises from the existence of 4 distinct DENV 49 serotypes with multiples genomic sequences. Nevertheless the existence of thousands of genotypes 50 for each serotype, the viruses have kept a great homology between the protein sequences of their 51 structural proteins (3). This phenomenon contrast with the one observed in the human 52 papillomavirus infection, which is caused by a DNA virus presenting over 170 serotypes (4). The 53 occurrence of viruses not belonging to the described 4 serotypes has been reported in Malaysia, 54 but this newcomer virus structure did not further propagate in the population (5). 55 56 Dengue virus are obliged to pass from one mammal host to one insect host to perpetuate the 57 infection. DENV infect several human tissues, encountering cells suitable for its amplification.58 Typically, endothelial cells of the liver; lung vascular endothelium cells, kidney tubules 59 multinucleated cells, spleen reactive lymphoid cells, macrophages, monocytes and lymphocytes 60 cells are the cells suitable for Virus infection (6). In the insect, the viral particle mainly infects 61 intestinal, circulatory and salivary gland cells (7). 62 63 In the mosquito environment, the virus mutation are dictated by the constraints of mosquito 64 interference RNA system evasion [8], [9]. The effect of immune defense protei...

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Prediction of dengue outbreaks in Mexico based on entomological, meteorological and demographic data

Cited by 22 publications

References 28 publications

Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Paediatric dengue infection in Cirebon, Indonesia: a temporal and spatial analysis of notified dengue incidence to inform surveillance

New Genotype Emergence of DENV are Constrained by the Double Host Selection, Reducing the Probability of Alternative Serotype Emergence

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