Relationship between epidemiologic surveillance with geo-climatic variables during Zika outbreak in Guerrero State, Mexico 2016

Abel Jimenez-Alejo, Ewry A. Zárate-Nahón, María L. Sampedro-Rosas, Sergio García-Ibáñez, José L. Rosas-Acevedo


Background: Zika like dengue and chikungunya represent public health problems. Cases of ZIKV infection are emerging in the Americas, from Argentina spread until Brazil and Colombia, later entry to Mexico and managed to establish itself in most of the states.

Methods: The cases (2016-2017) of epidemiological surveillance of the first outbreak of Zika in Guerrero were used. The incidence rates (IR) for each municipality were estimated (cases/100 000 inhabitants) to develop the first maps at the municipal and state level; which aimed to explore the relationship between Zika cases and geo-climatic variables.

Results: At January 3, 2017 in Guerrero State [epidemiological week (SE) 52 of the year 2016] were reported 861 confirmed ZIKV cases (10.06% of total registered cases at federal level). Guerrero State it was placed within the six states with the largest number of cases: Veracruz (1967), Yucatan (1284), Nuevo Leon (844), Chiapas (804) and Oaxaca (507); concentrated 73.26% (6 267/8 554) of the country's cases. In this study we identified the geo-environmental factors associated with ZIKV occurrence in each municipality of the Guerrero State: very high rain (1201-1460 mm), low elevation (2-398 masl) and high population density (≥62071 inhabitants/km2).

Conclusions: This study represents the first approach to Zika outbreak in Guerrero State. Although tests of spatial nature are not presented; the maps presented show how the characteristics by region have high influence and that the most affected areas were the coastal areas: Acapulco, Small Coast and Big Coast.


Zika, Infectious diseases, Epidemiology, Rainfall, México

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Rodriguez-Morales AJ. Zika: the new arbovirus threat for Latin America. J Infect Dev Ctries. 2015;9:684-5.

Secretaria de Salud, Subsecretaría de Prevención y Promoción de la salud, Dirección General de Epidemiologia, Sistema Nacional de Vigilancia Epidemiológica de Enfermedad por virus del Zika. Available at: attachment/file/334781/Cuadro_Casos_ZIKA_y_Emb_SE22_2018.pdf. Accessed on 18 May 2018.

Brownstein JS, Freifeld CC, Madoff LC. Digital disease detection--harnessing the Web for public health surveillance. N Engl J Med. 2009;360(21):2153-7.

Majumder MS, Kluberg S, Santillana M, Mekaru S, Brownstein JS. Ebola outbreak:media events track changes in observed reproductive number. PLoS currents. 2015;7.

Chunara R, Andrews JR, Brownstein JS. Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. Am J Trop Med Hyg. 2012;86(1):39-45.

Morin CW, Comrie AC, Ernst K. Climate and dengue transmission: evidence and implications. Environ Health Perspect 2013;121(11-12):1264-72.

Brady OJ, Golding N, Pigott DM, Kraemer MUG, Messina JO, Reiner RCJr, et al. Global temperature constraints on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission. Parasites Vectors. 2014;7:338.

Barrera R, Amador M, MacKay A. Population Dynamics of Aedes aegypti and Dengue as Influenced by Weather and Human Behavior in San Juan, Puerto Rico. PLOS Neglect Trop D. 2011;5:e1378.

Chowell G, Cazelles B, Broutin H, Munayco C. The influence of geographic and climate factors on the timing of dengue epidemics in Perú, 1994-2008. BMC Infect Dis. 2011;11:164.

Watts DM, Burke, D, Harrison, BA, Whitmire RE, Nisalak A. Effect of Temperature on the Vector Efficiency of Aedes aegypti for Dengue 2 Virus. Am J Trop Med Hyg. 1986;36:143–52.

Instituto Nacional de Estadística y Geografía, México. Available at: Accessed on June 14 2018.

Mena N, Troyo A, Bonilla-Carrión R, Calderón-Arguedas Ó. Factores asociados con la incidencia de dengue en Costa Rica. Rev Panam de Sal Pub 2011;29:234-42.

Le Thi Diem Phuong TT, Hanh T, Nam VS. Climate Variability and Dengue Hemorrhagic Fever in Ba Tri District, Ben Tre Province, Vietnam during 2004–2014. AIMS Public Health. 2016;3(4):769.

Wiwanitkit S, Wiwanitkit V. Predicted pattern of Zika virus infection distribution with reference to rainfall in Thailand. Asian Pacific J Tropical Med. 2016.

Rodriguez-Morales AJ, Ruiz P, Tabares J, Ossa CA, Yepes-Echeverry MC, Ramírez-Jaramillo V, et al. Mapping the ecoepidemiology of Zika virus infection in urban and rural areas of Pereira, Risaralda, Colombia, 2015–2016:Implications for public health and travel medicine. Travel Med Infect Dis. 2017;18:57-66.

Hii YL, Rocklöv J, Nawi NG, Tang CS, Pang FY, Sauerborn R. Climate variability and increase in intensity and magnitude of dengue incidence in Singapore, Glob Health Action. 2009;2(1):2036.

Fuentes-Vallejo, M. Space and space-time distributions of dengue in a hyper-endemic urban space:the case of Girardot, Colombia. BMC Infect Dis. 2017;17(1):512.

Pérez PN, Alcántara LC, Obolski U, de Lima MM, Ashley E, Smithuis F, et al. Measuring mosquito-borne viral suitability and its implications for Zika virus transmission in Myanmar. BioRxiv. 2017;231373.

Kuno G. Review of the factors modulating dengue transmission. Epidemiol Rev. 1995;17:321–35.

Rodríguez-Morales AJ, Haque U, Ball JD, García-Loaiza CJ, Galindo-Márquez ML, Sabogal-Román JA, et al. Spatial distribution of Zika virus infection in northeastern Colombia. Infez Med 2017;25(3):241-6.

Zambrano LI, Sierra M, Lara B, Rodríguez-Núñez I, Medina MT, Lozada-Riascos CO, et al. Estimating and mapping the incidence of dengue and chikungunya in Honduras during 2015 using Geographic Information Systems (GIS). J Infect Public Health. 2017;10(4):446-56.

Rodríguez-Morales AJ, Galindo-Márquez ML, García-Loaiza CJ, Sabogal-Román JA, Marín-Loaiza S, Ayala AF, et al. Mapping Zika virus disease incidence in Valle del Cauca. Infection. 2017;45(1):93-102.

Escobar-Mesa J, Gómez-Dantés H. Determinantes de la transmisión de dengue en Veracruz:un abordaje ecológico para su control. Salud pública de México. 2003;45:43-53.