The impact of climate change on the geographical distribution of two vectors of Chagas disease: implications for the force of infection

Abstract

Chagas disease, caused by the parasite Trypanosoma cruzi , is the most important vector-borne disease in Latin America. The vectors are insects belonging to the Triatominae (Hemiptera, Reduviidae), and are widely distributed in the Americas. Here, we assess the implications of climatic projections for 2050 on the geographical footprint of two of the main Chagas disease vectors: Rhodnius prolixus (tropical species) and Triatoma infestans (temperate species). We estimated the epidemiological implications of current to future transitions in the climatic niche in terms of changes in the force of infection (FOI) on the rural population of two countries: Venezuela (tropical) and Argentina (temperate). The climatic projections for 2050 showed heterogeneous impact on the climatic niches of both vector species, with a decreasing trend of suitability of areas that are currently at high-to-moderate transmission risk. Consequently, climatic projections affected differently the FOI for Chagas disease in Venezuela and Argentina. Despite the heterogeneous results, our main conclusions point out a decreasing trend in the number of new cases of Tr. cruzi human infections per year between current and future conditions using a climatic niche approach.

Ecological niche modelling in triatomines– abusus non tollit usum : a reply to Gutiérrez (2016)

“…In [1], data quality controls were applied: R. prolixus was deleted from Bolivia and southern Amazonia, T. infestans was pooled with T. melanosoma, and extended in Bolivia; coordinates were deleted using a database with georeferenced water bodies. Elevational false positives claimed by Gutierrez [2] are not such (by mistake, Medone et al [1] reported the altitudinal limits given by Carcavallo et al [3] instead of the ones of the data used).…”

“…Lack of prediction errors from the use of confirmed occurrences was criticized by Gutierrez [2]; however, MAXENT was not run with confirmed presence data: only predictions from range maps with confirmed presences were checked. We apologize for not reporting the geographical projection of the models, which was the Americas, between 44 N and 247 S, and 234 E and 2125 E.The study regions should not include areas that cannot be accessed due to dispersal problems, but there are some caveats in triatomines: (i) triatomines are detectable in restricted time/space-windows (time of day or year, type of habitat), affecting the pseudo-presence/pseudo-absence problem more than inaccessible areas; (ii) sampling triatomines is biased: most sampling is associated with rural houses in detriment to sylvatic habitats ('biased in environmental dimensions' [6]), inducing more noise than the pseudo-presence problem; (iii) the use of domiciliated microhabitats dampens climatic effects [7,8], minimizing pseudopresences (areas nearby confirmed presence have a higher possibility of being pseudo-absence than pseudo-presence); and (iv) in addition to their own dispersal capacities, triatomines are also transported by humans and animals, resulting in range shifts that outweigh the pseudo-presence/pseudo-absence problems.The pseudo-presence and background problems raised by Gutierrez [2] are possibly the strongest criticism to [1], regardless of the use of surveys and range maps to estimate richness results in under-and overestimation, respectively [9]. Is not complying with the use of confirmed occurrences a serious violation in triatomines?…”

“…The pseudo-presence and background problems raised by Gutierrez [2] are possibly the strongest criticism to [1], regardless of the use of surveys and range maps to estimate richness results in under-and overestimation, respectively [9]. Is not complying with the use of confirmed occurrences a serious violation in triatomines?…”

“…

In [1], the vectorial risk of Chagas disease transmission was estimated from the climatic suitability expected for Rhodnius prolixus and Triatoma infestans by year 2050 in Argentina and Venezuela using ecological niche modelling (ENM), and Gutierrez [2] claimed that the nature of the data and the study regions might invalidate the conclusions. Although this warning is fit and welcomed, in triatomines and for particular goals the use of ENM, though not complying with some methodological prescriptions, can be justified.

In [1], data quality controls were applied: R. prolixus was deleted from Bolivia and southern Amazonia, T. infestans was pooled with T. melanosoma, and extended in Bolivia; coordinates were deleted using a database with georeferenced water bodies.

…”

“…Although this warning is fit and welcomed, in triatomines and for particular goals the use of ENM, though not complying with some methodological prescriptions, can be justified.In [1], data quality controls were applied: R. prolixus was deleted from Bolivia and southern Amazonia, T. infestans was pooled with T. melanosoma, and extended in Bolivia; coordinates were deleted using a database with georeferenced water bodies. Lack of prediction errors from the use of confirmed occurrences was criticized by Gutierrez [2]; however, MAXENT was not run with confirmed presence data: only predictions from range maps with confirmed presences were checked.…”