Comments on: On the Seasonal Occurrence and Abundance of the Zika Virus Vector Mosquito Aedes Aegypti in the Contiguous United States Sat, 27 Oct 2018 04:18:43 +0000 hourly 1 By: monaghan Sun, 14 Aug 2016 15:55:09 +0000 Good question. Since we published this paper, Hahn et al. (1) published updated U.S. county-level records of Aedes aegypti and Aedes albopictus presence for the past ~20 years. Based on their data, four counties in North Carolina have reported Aedes aegypti presence, though each occurrence was only reported in one year (i.e, to the best of our knowledge the observations have not been repeated in any county in NC as of yet). The four counties are:

Chatham (year 2004)
Hoke ( year 2003)
Scotland (year 2006)
Swain ( year 2002)

The report in western NC you inquired about is Swain (I believe this is the same record the dot on our map is based on). Asheville is located in a different county (Buncombe), so I am not certain which town the Swain report is from.

(1) Hahn, M. B., Eisen, R. J., Eisen, L., Boegler, K. A., Moore, C. G., McAllister, J., … & Mutebi, J. P. (2016). Reported Distribution of Aedes (Stegomyia) aegypti and Aedes (Stegomyia) albopictus in the United States, 1995-2016 (Diptera: Culicidae). Journal of Medical Entomology, tjw072.

By: simunye36 Wed, 10 Aug 2016 15:04:45 +0000 Great article! In Fig S1, the red dot representing Aedes Aegypti in Western North Carolina…what city is that in? Is that Asheville?

By: monaghan Sun, 29 May 2016 22:05:17 +0000 No, we did not simulate Zika virus transmission in this study.

By: monaghan Sun, 29 May 2016 22:04:10 +0000 The Aedes aegypti seasonality results are applicable at approximately the metropolitan scale, for each of the 50 cities for which we performed model simulations of mosquitoes. To explain, we interpolated daily gridded meteorological fields to the published coordinates for each city (latitude and longitude — shown in Table 1), and then used each resulting weather time series to drive mosquito life cycles models and simulate Aedes aegypti seasonal abundance. The model results do not account for microclimatic variability across each city, but rather represent the ‘average’ climatic conditions in each city. For cities that have substantial climatic variability across them — e.g., due to mountainous terrain or marine effects — the results may be less representative for suburban areas at higher elevations or far inland from water bodies. The results are not considered valid outside of cities, in part because Aedes aegypti favors urban areas.

By: michaelz Sun, 29 May 2016 16:55:52 +0000 Are there projections of number of cases based on this data?

By: michaelz Wed, 25 May 2016 15:43:47 +0000 We are developing a zip code level data set from this information. What is the typical radius from city to project? use MSA perhaps? Or is this study just applicable to zip codes within a city?

By: monaghan Mon, 04 Apr 2016 16:50:55 +0000 Thanks very much for your interest in this work and for your thoughtful and detailed comments. Your views certainly corroborate our own lengthy discussion summarizing many of the weaknesses and uncertainties in the model simulations of Ae. aegypti. Our goals in publishing this paper are:

1) to provide a first-cut at mapping the seasonality of Ae. aegypti in the contiguous United States – primarily as a function of climatic suitability since we know little about parameters such as food and egg dynamics here – with the hopes that others will be motivated to refine the result; and

2) to examine potential Ae. aegypti populations in the context of other ZIKAV risk factors that are equally or more important; i.e., travel related introduction, human exposure, previous local-transmission of Aedes viruses.

With respect to the goal #1, we particularly hope that our results will motivate more standardized and widespread observation-based surveillance for Aedes mosquitoes in the United States. While additional model refinements/results would certainly be useful – and we would be happy to provide you with the meteorological fields to run the AedesBA model for the 50 U.S. locations – no matter how much system complexity and realism they depict, models will always be subject to inherent uncertainties due to poorly constrained parameters (e.g., see our investigation of nearly 10,000 different parameter combinations and how they influence DENV outcomes in DyMSiM in Morin et al. (1)). Without vastly more observations of Ae. aegypti in the United States (and elsewhere), we will continue to have highly uncertain results regardless of model complexity.

(1) Morin, C.W., A.J. Monaghan, M.H. Hayden, R. Barrera, and K.C. Ernst, 2015: Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR. PLoS Negl. Trop. Dis., 9, e0004002.

By: hgsolari Mon, 28 Mar 2016 00:46:07 +0000 The paper presents results comparing two models for Aedes aegypti (DyMSIM and SkeeterBuster) as well as field data. It is evident from the Fig. 3 that the models’ predictions are in agreement between them but they are a far cry for field data despite being monthly reports (i.e., highly averaged in time). The results from the models are expected to be similar since they implement the same ideas taken from Focks original model (ref. 43 in the paper), namely synchronous cohorts and development determined by accumulation of heat. None of them includes temperature dependent-food-dynamics and despite SkeeterBuster producing spatial descriptions it has been restricted to a minimal patch of 10 households.
Aedes aegypti larvae eats bacteria, yeast and microbiota in general. The reproduction of all of them are highly sensible to temperature. Case by case, this dependency can be accounted for by suitable changes in the parameters when answering the question: is there a set of parameters that would allow us to accept the collected data as an outcome of the model? Calibration (the name of the procedure) cannot distinguish between the correct and the wrong reasons and then, the inferred parameters cannot be used in other situations.
Lack of a relevant spatial description almost certainly produce extinction of the mosquito in temperate climates (see below). To overcome this difficulty the paper introduces the release of 80-100 eggs per container to avoid extinction. Reintroduction of Aedes aegypti is a fact, but more often than not, it is produced in the form of eggs. More frequently, eggs overwinter (1). How would those eggs reach the simulated patch any time in the year as needed by the simulations? The method introduces spatial homogeneity where there is no such and it will increase spring populations by making all breeding sites available. It comes then as no surprise the gross failure of the simulations shown by Fig. 3 when comparing to collected data. Lack of temperature-dependent-food-dynamics is expected to predict longer favorable seasons when food is provided at a constant rate. Such expected difference with collected data can also readily be seen in Fig. 3 of the paper.
There is a different lineage of models (2-7) (let us call them AedesBA) that in part were born under the concern that Fock’s model presented shortcuts that could invalidate its use in cities with temperate climate. Such models sustain populations of Aedes aegypti without the need of re‑introducing eggs to avoid extinction. AedesBA models coupled with observations and experiments have been able to challenge the idea of cohort in which SkeeterBuster and DyMSIM are based (6) and have shown the need to consider food as a dynamical variable. They have also shown that the extinction-repopulation within-the-city dynamics observed in Buenos Aires (a temperate climate city) is to be expected (2, 7).
When used as the basis for dengue simulations, AedesBA has been able to predict the occurrence of dengue epidemics at a temperate climate city without precedents of such epidemics, the characteristics of the epidemics (7) as well as reproducing historic events (8).
Currently, there is an ongoing dengue epidemic outbreak in Buenos Aires city which is reaching its maximum number of cases per day at the time predicted by the models (3), a prediction that has allowed the public health authorities to be ready for the the expected stress to the public health system. A previous epidemic outbreak (2009) was predicted in (3) shortly before its occurrence. However, the situation at that time was addressed by the health authorities using Fock’s model (9) and the possibility of an epidemic outbreak was disregarded. The event speaks loudly about the importance of using models within the scope they were intended for and the need of a critical evaluation of the hypothesis incorporated into the models. Failures of simulations should not be ignored but rather, they should trigger inquiries aimed at improving the models, otherwise we will be bound to predict from ignorance.

1. Sylvia Fischer, Iris Soledad Alem, María Sol De Majo, Raúl Ernesto Campos, Nicolás Schweigmann. Cold season mortality and hatching behavior of Aedes aegypti L. (Diptera: Culicidae) eggs in Buenos Aires City, Argentina. Journal of Vector Ecology, 36 (1), (2011)
2. M Otero, H. G. Solari and N. Schweigmann. A stochastic population dynamics model for Aedes aegypti: formulation and application to a city with temperate climate. Bulletin of Mathematical Biology, 68, 1945-1974 (2006).
3. M. J. Otero and H. G. Solari. Stochastic eco-epidemiological model of dengue disease transmission by Aedes aegypt mosquito. Mathematical Biosciences, 223, 32-46 (2010).
4. V Romeo Aznar, Marcelo Otero, Maria Sol de Majo, Sylvia Fischer and Hernán G Solari. Modeling the complex hatching and development of Aedes aegypti in temperate climates. Ecological Modelling 253, 44-55 (2013).
5. V Romeo Aznar, M S de Majo, S Fischer, D Francisco, MA Natiello and HG Solari. A model for the development of Aedes (Stegomyia) aegypti as a function of the available food. Journal of Theoretical Biology, 365, 311-324, 2015.
6. M. J. Otero and H. G. Solari. Stochastic eco-epidemiological model of dengue disease transmission by Aedes aegypti mosquito. Mathematical Biosciences, 223, 32-46 (2010)
7. M L Fernández and M Otero and N Schweigmann and H G Solari, A mathematically assisted reconstruction of the initial focus of the yellow fever outbreak in Buenos Aires (1871). Papers in Physics 5, 050002, 2013,
8. A E Carbajo and S M Gomez and S I Curto and N Schweigmann, Variación Espacio Temporal del Riesgo de Transmisión de Dengue en la Ciudad de Buenos Aires, Medicina 64, 231-234 (2004)
9. A Seijo, Romer, M Espinosa, J Monroig, S Giamperetti, D Ameri and L Antonelli. Brote de Dengue Autóctono en el Area Metropolitana Buenos Aires. Experiencia del Hospital de Enfermedades Infecciosas F. J. Muñiz. Medicina 69, 593-600, (2009).

By: monaghan Fri, 25 Mar 2016 00:29:11 +0000 That’s a very good question. We are exploring the feasibility to use seasonal climate forecasts to examine potential Aedes aegypti abundance in the forthcoming months. If we move forward, we would likely expand the geographic scope to include cities throughout the Americas where ongoing ZIKAV transmission is occurring (e.g., in Brazil, Colombia, etc.).

By: Jean-Paul Chretien Wed, 23 Mar 2016 19:24:23 +0000 Great paper! Are you considering applying 2016 seasonal climate forecasts to the model, to see how El Nino or other anomalies could affect abundance?