Parameter estimates of the 2016-2017 Zika outbreak in Costa Rica: An Approximate Bayesian Computation (ABC) approach

Sánchez, Fabio; Barboza, Luis A.; Vásquez, Paola

doi:10.3934/mbe.2019136

Cited by 10 publications

(9 citation statements)

References 66 publications

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“…Despite these limitations, results from this study, suggest that large-scale climate and local weather factors can potentially be used as effective tools in the decision-making process of local public health-authorities. It also shows, as in previous studies [22,57], the importance of statistical models as instruments in the rapid analysis of information generated by different local and national institutions, as they could enhance the management of early epidemic response and preventive measures in Costa Rica. However, the development of tailored climate products and services that can be fully mainstreamed into public health decision-making, is a collaborative process that would require interinstitutional integration of expertise and data [68], including the Ministry of Health, the National Meteorological Institute and the National Census Bureau, among others, collaboration that could have a positive impact in the management not only of mosquito-borne diseases, but all the other climate-sensitive diseases that affect the country.…”

Section: Discussionsupporting

confidence: 71%

Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach

Vásquez

Loría

Sánchez

et al. 2019

RMTA

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Climate has been an important factor in shaping the distribution and incidence of dengue cases in tropical and subtropical countries. In Costa Rica, a tropical country with distinctive micro-climates, dengue has been endemic since its introduction in 1993, inflicting substantial economic, social, and public health repercussions. Using the number of dengue reported cases and climate data from 2007-2017, we fitted a prediction model applying a Generalized Additive Model (GAM) and Random Forest (RF) approach, which allowed us to retrospectively predict the relative risk of dengue in five climatological diverse municipalities around the country.In Costa Rica, as in most of the Americas, the reintroduction and dissemination of Aedes aegypti took place during the 1970s [19,52]. However, it was until September 1993 that the first dengue cases were reported on the Pacific coast [43] when autochthonous transmission of DENV-1 was confirmed [47]. Since then, three of the four serotypes of the virus (DENV-1, DENV-2, DENV-3) have circulated the national territory, with peaks of transmission that exhibit both seasonal and inter-annual variability [43]. Over 370,000 suspected and confirmed cases have been reported by the Ministry of Health [43], of which, more than 45,000 have required hospital care [10].With the high burden that DENV infections represent to the country, where, as in most endemic regions, traditional control measures have proven ineffective to sustain long-term trends in cases-reduction [21], surveillance, prevention, and control of dengue is a public health challenge that requires specific and cost-effective strategies [65]. In this effort, and as a worldwide strategy for reducing dengue incidence, the World Health Organization (WHO) is highlighting the importance of determining sensitive indicators for dengue outbreaks as early warning signals [65], in which climate and weather variables have shown to play an essential role [31,18,20]. Specifically, variables such as temperature, precipitation, humidity and El Niño Southern Oscillation (ENSO), have been closely correlated to the occurrence of dengue cases and the seasonality of dengue epidemics [16,12,69].Changes in these climate conditions influence the ecology of the DENV by modulating vector mosquito population dynamics, viral replication, and transmission, as well as, human behavior [7,48]. It has been observed that transmission of DENV occurs between 18 • C -34 • C, with maximal transmission peaks in the range of 26 • C -29 • C [46]. At higher temperatures, the duration of the life cycle decreases [72,60], biting activity increases [62,55,20] and the extrinsic incubation period becomes shorter [15,70], prolonging the infective days of the mosquito [20]. Precipitation provides habitat for the aquatic stages of the life cycle and influences vector distribution [48]. Moreover, heavy rainfall events can decrease mosquito abundance by flushing larvae from containers [36,4], and drought events can increase household water containers [61]. Humidity also affects...

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Section: Discussionsupporting

confidence: 71%

Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach

Vásquez

Loría

Sánchez

et al. 2019

RMTA

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“…At this stage, it is also necessary, that modelers and health authorities involve knowledge translation activities that will allow the general community to better comprehend their part in the fight against these diseases [45]. These education strategies have the potential to be more targeted thanks to the information that the different models can provide about the unique characteristics of each specific region or community in the country, for example the increased risk of Zika infections among those people that spent most of the time at home inside their homes as opposed to those who spent a substantial amount of time outside due to work or other activities, demonstrate in [30]. Results that go in hand with mosquito behaviour.…”

Section: Resultsmentioning

confidence: 99%

“…With the combination of a Bayesian statistical approach and a single-outbreak mathematical model with sexual transmission, authors in [8] described the overall dynamics of Zika during 2016-2017 outbreak in Costa Rica. The estimated parameters were the mosquito’s average lifespan, the mosquito biting rate, and the per-capita diagnosis rate.…”

Section: Methodsmentioning

confidence: 99%

“…The Bayesian statistical approach was also explored in [30] by means of a single-outbreak model with sexual transmission mathematical model that describes the overall dynamics of Zika during 2016-2017 in Costa Rica. The authors define as parameters to estimate the average life-span of mosquitoes, the mosquito biting rate and the per-capita diagnosis rate.…”

Section: Approximate Bayesian Computationmentioning

confidence: 99%

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Mathematical and Statistical models as tools for the control of mosquito-borne diseases: The experience of Costa Rica

Sánchez

Vásquez

et al. 2021

Preprint

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“…Costa Rica reported one of the highest numbers of confirmed cases of Zika virus (ZIKV) during the Zika emergency from 2015-2018 in the Central America region (PAHO 2018). Despite control efforts, ABD persists in Limon and Puntarenas provinces, where the highest number cases of ZIKV of Costa Rica were reported (Sanchez et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Co-occurrence of kdr Mutations V1016I and F1534C and Its Association With Phenotypic Resistance to Pyrethroids in Aedes aegypti (Diptera: Culicidae) Populations From Costa Rica

Zardkoohi

Castañeda

Lol

et al. 2019

Journal of Medical Entomology

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Aedes aegypti (Linnaeus, 1762) is considered the most important mosquito vector species for several arboviruses (e.g., dengue, chikungunya, Zika) in Costa Rica. The primary strategy for the control and prevention of Aedes-borne diseases relies on insecticide-based vector control. However, the emergence of insecticide resistance in the mosquito populations presents a significant threat to these prevention actions. The characterization of the mechanisms driving the insecticide resistance in Ae. aegypti is vital for decision making in vector control programs. Therefore, we analyzed the voltage-gated sodium channel (VGSC) gene for the presence of the V1016I and F1534C kdr mutations in Ae. aegypti populations from Puntarenas and Limon provinces, Costa Rica. The CDC bottle bioassays showed that both Costa Rican Ae. aegypti populations were resistant to permethrin and deltamethrin. In the case of kdr genotyping, results revealed the co-occurrence of V1016I and F1534C mutations in permethrin and deltamethrin-resistant populations, as well as the fixation of the 1534C allele. A strong association between these mutations and permethrin and deltamethrin resistance was found in Puntarenas. Limon did not show this association; however, our results indicate that the Limon population analyzed is not under the same selective pressure as Puntarenas for the VGSC gene. Therefore, our findings make an urgent call to expand the knowledge about the insecticide resistance status and mechanisms in the Costa Rican populations of Ae. aegypti, which must be a priority to develop an effective resistance management plan.

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Parameter estimates of the 2016-2017 Zika outbreak in Costa Rica: An Approximate Bayesian Computation (ABC) approach

Cited by 10 publications

References 66 publications

Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach

Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach

Mathematical and Statistical models as tools for the control of mosquito-borne diseases: The experience of Costa Rica

Co-occurrence of kdr Mutations V1016I and F1534C and Its Association With Phenotypic Resistance to Pyrethroids in Aedes aegypti (Diptera: Culicidae) Populations From Costa Rica

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