SAIFR:2140

Detecting climate drivers of malaria using a causality criterion

(2020). Detecting climate drivers of malaria using a causality criterion. ICTP South American Institute for Fundamental Research. https://scivideos.org/index.php/ictp-saifr/2140

Detecting climate drivers of malaria using a causality criterion. ICTP South American Institute for Fundamental Research, Mar. 03, 2020, https://scivideos.org/index.php/ictp-saifr/2140 

          @misc{ scivideos_SAIFR:2140,
            doi = {},
            url = {https://scivideos.org/index.php/ictp-saifr/2140},
            author = {},
            keywords = {ICTP-SAIFR, IFT, UNESP},
            language = {en},
            title = {Detecting climate drivers of malaria using a causality criterion},
            publisher = { ICTP South American Institute for Fundamental Research},
            year = {2020},
            month = {mar},
            note = {SAIFR:2140 see, \url{https://scivideos.org/index.php/ictp-saifr/2140}}
          }
Renato Coutinho
Talk numberSAIFR:2140
Source RepositoryICTP – SAIFR
Collection
Talk Type Conference
Subject

Abstract

Authors: K. Laneri*, B. Cabella*, P.I. Prado, R.M. Coutinho**, R.A. Kraenkel I'll quickly introduce the Convergent Cross-Mapping (CCM) criterion to investigate causality between two time series. Than I'll present an analysis of the potential environmental drivers of malaria cases in Northwestern Argentina, and discuss plausible interpretations of these results. We have inspected causal links between malaria and climatic variables, based on 12 years of weekly malaria /P. vivax/ cases in Tartagal, Salta, Argentina—at the southern fringe of malaria incidence in the Americas—together with humidity and temperature time-series spanning the same period. Our results show that there are causal links between malaria cases and both maximum temperature, with a delay of five weeks, and minimum temperature, with delays of zero and twenty two weeks. Humidity is also a driver of malaria cases, with thirteen weeks delay between cause and effect. Furthermore we also determined the sign and strength of the effects. These results might be signaling processes operating at short (below 5 weeks) and long (over 12 weeks) time delays, corresponding to effects related to parasite cycle and mosquito population dynamics respectively. The non-linearities found for the strength of the effect of temperature on malaria cases make warmer areas more prone to higher increases in the disease incidence. Moreover, our results indicate that an increase of extreme weather events could enhance the risks of malaria spreading and re-emergence beyond the current distribution. Both situations, warmer climate and increase of extreme events, will be remarkably increased by the end of the century in thishot spot of climate change. * joint first authors** speaker