Modeling of leptospirosis outbreaks in relation to hydroclimatic variables in the northeast of Argentina
Andrea Alejandra Gómez,
María Soledad López,
Gabriela Viviana Müller,
Leonardo Rafael López,
Walter Sione,
Leonardo Giovanini
Affiliations
Andrea Alejandra Gómez
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro de Estudios de Variabilidad y Cambio Climático (CEVARCAM), Universidad Nacional del Litoral (UNL). Ciudad Universitaria, 3000, Santa Fe, Argentina; Corresponding author.
María Soledad López
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro de Estudios de Variabilidad y Cambio Climático (CEVARCAM), Universidad Nacional del Litoral (UNL). Ciudad Universitaria, 3000, Santa Fe, Argentina
Gabriela Viviana Müller
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro de Estudios de Variabilidad y Cambio Climático (CEVARCAM), Universidad Nacional del Litoral (UNL). Ciudad Universitaria, 3000, Santa Fe, Argentina
Leonardo Rafael López
Barcelona Institute for Global Health, Doctor Aiguader, 88, 08003, Barcelona, Spain
Walter Sione
Facultad de Ciencia y Tecnología de la Universidad Autónoma de Entre Ríos (FCYT-UADER), Ruta 11 - Km 10,5, 3100, Oro Verde, Entre Ríos, Argentina
Leonardo Giovanini
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) – Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional (Sinc(i)), Universidad Nacional del Litoral (UNL). Ciudad Universitaria, 3000, Santa Fe, Argentina
The transmission of leptospirosis is conditioned by climatic variables. In northeastern Argentina leptospirosis outbreaks occur mainly in coincidence with periods of abundant precipitation and high hydrometric level. A Susceptible-Infectious-Recovered Epidemiological Model (SIR) is proposed, which incorporates hydroclimatic variables for the three most populated cities in the area (Santa Fe, Paraná and Rosario), during the 2009–2018 period. Results obtained by solving the proposed SIR model for the 2010 outbreak are in good agreement with the actual data, capturing the dynamics of the leptospirosis outbreak wave. However, the model does not perform very well in the last months of the year when isolated cases appear outside the outbreak periods, probably due to non- climatic factors not explicitly considered in the present version of the model. Nevertheless, the dynamic modeling of infectious diseases considering hydroclimatic variables constitutes a climatic service for the public health system, not yet available in Argentina.
