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DISCLAIMER

This paper was submitted to the Bulletin of the World Health Organization and was posted to the Zika open site, according to the protocol for public health emergencies for international concern as described in Christopher Dye et al. (http://dx.doi.org/10.2471/BLT.16.170860 ).

The information herein is available for unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited as indicated by the Creative Commons Attribution 3.0 Intergovernmental Organizations licence (CC BY IGO 3.0).

RECOMMENDED CITATION

Rodriguez-Morales AJ, Haque U, Ball JD, García-Loaiza CJ, Galindo-Marquez ML, Sabogal-Roman JA et al. Spatial distribution of Zika virus infection in northeastern [Submitted]. Bull World Health Organ E-pub: 29 Apr 2016. doi: http://dx.doi.org/10.2471/BLT.16.176529

Spatial distribution of Zika virus infection in northeastern Colombia Alfonso J Rodriguez-Morales a,Ubydul Haque c, Jacob D Ball d, Carlos Julian García-Loaiza a, Maria Leonor Galindo-Marquez a, Juan Alejandro Sabogal- Roman a, Santiago Marin-Loaiza a, Andrés Felipe Ayala a, Carlos O. Lozada- Riascos a, Fredi A. Diaz-Quijano d & Jorge L Alvarado-Socarras b aPublic Health and Infection Research Group, Faculty of Health Sciences, Universidad Tecnologica de Pereira, Carrera 27 #10-02 Barrio Alamos, Risaralda, Colombia, 660003 bOrganización Latinoamericana para el Fomento de la Investigación en Salud (OLFIS), 13 14 , Santander, Colombia cDepartment of Geography, University of Florida, Gainesville, Florida, USA dEmerging Pathogens Institute, University of Florida, Gainesville, Florida, USA eDepartment of Epidemiology, Faculty of Public Health, Universidade de São Paulo, São Paulo, Brazil Correspondence to Alfonso J. Rodriguez-Morales (email: [email protected]) (Submitted: 28 April 2016 – Published online: 29 April 2016)

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Abstract

Objective : In this study, we investigated the weekly reported spatio-temporal distribution and topographic risk factors for Zika virus (ZIKV) infection in Northeastern Colombia.

Methods : Weekly reported surveillance data, including clinical, suspicious and confirmed cases from the ongoing ZIKV epidemic in the Santander and Norte de Santander departments ( Santanderes ), Colombia were used to estimate cumulative incidence rates. Spatial analysis was performed to develop hot spot maps and to identify spatial topographic risk factors for infection.

Results : From January 1, 2016 to March 19, 2016, 11,515 cases of ZIKV were reported in Santanderes , with cumulative rates of 316.07 cases/100,000 population for the region (representing 18.5% of the cases of the country). Five municipalities (four in Norte de Santander ) reported high incidence of ZIKV infection (>1,000 cases/100,000 pop) ; these municipalities are close to the border with Venezuela. Most of the cases reported occurred mainly in low altitude areas, and persistent hot spots were observed. Higher infection rates were reported in northeastern part of the study area.

Conclusions : Use of risk maps can help guide decisions for the prevention and control of ZIKV. Hotspots on the boarder of Colombia and Venezuela can have implications for international spread. 3

Introduction Zika virus (ZIKV) infection is causing epidemics in Latin America. 1 Colombia has officially reported a total of 58,838 cases of ZIKV infection in the first 32 epidemic weeks (21 in 2015 and 11 in 2016). 2 According to the Pan American Health Organization (PAHO) and the World Health Organization (WHO), Colombia has fewer cases than Brazil in terms of absolute number of infections (58,838 cases, 4% laboratory confirmed in Colombia compared to 72,596 cases, 0.74% laboratory confirmed in Brazil).3, 4 However, Colombia has a higher per capita incidence rate (IR) than Brazil due to its smaller population size (209,157,170 pop, IR = 34.71 cases/100,000 population in Brazil; 48,747,632 population, IR=120.70 cases/100,000 population in Colombia). 4 The ZIKV incidence rate is 3.5 times higher in Colombia than in Brazil. Thus, Colombia currently faces the greatest burden of disease for ZIKV, worldwide.

Up-to-date surveillance data are crucial to better understand ZIKV epidemiology, including the distribution of disease burden across landscapes and time. Spatial epidemiological analysis can produce risk maps that can be used to describe communities at higher risk for infection to prioritize interventions and to advise travel policies for visitors.

Previous studies have reported on the burden of ZIKV infection in Colombia and used geographical information systems (GIS) to produce maps for La Guajira (northern Colombia) and for Tolima (central Colombia).5, 6 No GIS-based epidemiological maps of ZIKV have been developed for Santander and Norte de Santander (together, Santanderes ), two departments in northeastern Colombia with the highest incidence rates. 7 Because this region shares a border with Venezuela, a country where ZIKV incidence is expected to be high but is not well-characterized 7, the observed incidence rates in Santanderes could have implications for the international spread of the disease.

Information about the spatio-temporal distribution and risk factors for ZIKV is limited in Colombia,5,6 particularly in northeastern part of the country. This region has been significantly affected by the current outbreak as evidenced by Norte de Santander having the highest number of reported cases in 2016 (8,484 as of March 19, 2016).2 Here, we estimated the cumulative incidence rate of ZIKV infection and created risk maps for Santander and Norte de Santander regions.

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Methods Surveillance data on weekly reported ZIKV cases, including both laboratory confirmed and clinically suspected cases, for 2016 were reported by the National Institute of Health, Colombia 7 and were used to estimate cumulated incidence rates. Population data for 2016 from the 2005 National Colombian Census with population annual projections (www.dane.gov.co) was used as denominator to estimate per capita ZIKV infections (cases/100,000 population) in each Santander and Norte de Santander , and together for the Santanderes .

Diagnosis Diagnosis of ZIKV infection included laboratory and/or syndromic surveillance (clinical definition of fever, rash, conjunctivitis and arthralgias in a municipality with previously ZIKV circulation, at least one case confirmed by real time-polymerase chain reaction, RT-PCR). 7 Until April 15, 2016, there were no serological tests available for diagnosis of ZIKV infection in Colombia, only RT-PCR is available. Those fitting the clinical definition but who were diagnosed in a municipality without laboratory-confirmed cases, were considered “suspected”.

Data for this study were gathered from 127 primary notification units, one per municipality, and later consolidated at the department’s level for Santander and Norte de Santander .

Spatial analysis Microsoft Access (version 365)® was used to design the spatial database, and to import incidence rates for municipalities to the GIS software Kosmo Desktop, which was used to develop the maps (Figure 2). Geographic data (municipalities and department polygons) required for the department were provided by the Regional Information System of the Coffee-Triangle region (http://www.sirideec.org.co/). The 90-meter resolution Shuttle Radar Topographic Mission Digital Elevation Model was downloaded from NASA’s website. Road and rail ways and water bodies were downloaded from DIVA-GIS.8 The shape files (based on official cartography) of municipalities and communes were linked to the database. We developed risk maps in the municipalities of both Santander and Norte de Santander . ArcGIS 10.2 and Kosmo ® 3.1 were used to generate the risk maps. Space-time pattern mining tools in ArcGIS Pro 1.1 were used for hot spots analysis. All municipalities within Santanderes over the 12 weeks were imported into this tool and analyzed for 5

spatial correlations across space and time to identify clusters of ZIKV infection over space and time. Each centroid location in the department was assigned 10,000 meter × 10,000 meter spanning area.

Results Through March 19, 2016, Santanderes have reported 11,515 cases (6.8% were confirmed by RT- PCR and 84% were suspected cases); 22% of these cases came from Santander and 77% from Norte de Santander . The cumulative incidence rate of ZIKV across all 127 municipalities within the two departments for all reported cases (both confirmed and suspected) was 316 cases/100,000 populations. The cumulative incidence rate for laboratory-confirmed cases was 21 cases/100,000 population (Figure 2). In Norte de Santander , cumulative incidence rates ranged from 0 to 4,535 cases/100,000 population in each municipality; Santiago municipality had the highest cumulative incidence rate (4,535 cases/100,000 population), followed by (1,686 cases/100,000 population), (1,182 cases/100,000 population) and (1,046 cases/100,000 population) (Figure 2 and Supplement Tables 1 & 2). Cucuta , the capital of Norte de Santander , shares a border with Venezuela and contributed 64% of total cases in the department and 54% in the Santanderes (Supplement Table 1 & 2, Figure 1) with a cumulative incidence rate of 904 cases/100,000 population. Out of the 40 municipalities in Norte de Santander , only three did not report any suspected or confirmed ZIKV cases (Supplement Table 1).

Capitanejo is the municipality in Santander with the highest cumulative incidence rate, 2,471 cases/100,000 population (Figure 2). Bucaramanga , the capital of Santander , contributed 30% of all cases in the department (Figure 2) and 4.5% of cases in the entire Santanderes region. Out of the 87 municipalities in this department, 41 have not reported any ZIKV cases (Figure 3, Supplement Table 1 & 2).

Persistent hot spots, defined as points where at least 90% of the time step intervals are hot, with no trend up or down, were reported in the northern and southern parts of the study area and in altitudes around 2000 to 2800 meter (Figures 4). Municipalities in higher altitudes (>2800 meter) did not report any ZIKV cases. Presence of bodies of water, railways and road networks were not statistically significantly associated with the spread of ZIKV in Santanderes and Norte de Santander . 6

Discussion In northeastern region of Santanderes , the burden of ZIKV infection has been concentrated in the eastern area, with Cucuta , a municipality close to the border with Venezuela, presenting more than half of all cases in the two departments. Municipalities such as Cucuta , that share common border with Venezuela, tend to have high levels of cross-border movement,7 which can pose a significant risk for the international spread of ZIKV (Figure 2). Although Zika arrived in Colombia at the end 2015, regions outside the Caribbean coast, such as Santanderes , have largely been affected during 2016.

These results suggest that the Santanderes region is a high risk area for ZIKV infection; it is already endemic of dengue and CHIKV, which share the same mosquito vector.9, 10 Among cases in Santanderes , 2,475 (22 %) were in pregnant women (393 confirmed by RT-PCR for ZIKV). 2 Detailed maps for ZIKV in pregnant women would be useful for describing the epidemiology of ZIKV-associated outcomes, such as microcephaly, other birth defects and Guillain-Barré syndrome.11

Approximately 92% of cases in this study were diagnosed based on clinical signs and symptoms, rather than laboratory testing. Strengthening the surveillance system and diagnostic capacity are critical for improving the public health responses to ZIKV in high-risk zones. Colombian Ministry of Health should target ZIKV persistent hot spots and high-risk municipalities. This study also reported the presence of ZIKV in every municipality except in those higher than 2800 meters above sea level, which was expected because the vectors (mainly Aedes aegypti and A. albopictus ) are have difficulty surviving and reproducing in higher altitudes. Similarly, there are fewer people living in the high altitude areas.

Further research about ZIKV transmission dynamics in Colombia, is critical for informing control efforts. As already reported, ZIKV can spread through sexual contact 12 and blood transfusion;13 mass awareness campaign by radio, television, mass public health alerts to people via mobile communication and newspaper advertisement may help the public understand and limit their risk behaviors associated with infection. 1,4

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We suggest employing real-time GIS-based epidemiological maps to visualize ZIKV transmission dynamics at the national, departmental and municipality levels to identify intervention priorities. Future study should focus on clinical symptoms for all PCR positive cases along with geocoded locations, travel history and socio demographic risk factors. Additionally, further work should quantify the effect that cross-border movement has on the distribution of ZIKV in Colombia and all of Latin America, to allow for the development emergency preparedness protocols in newly affected areas.5, 6, 14, 15

Acknowledgement Universidad Tecnológica de Pereira and Organización Latinoamericana para el Fomento de la Investigación en Salud. Ubydul Haque was supported in part by the Emerging Pathogens Institute at the University of Florida and the College of Liberal Arts and Sciences, as part of the University of Florida Pre-eminence Initiative.

Funding : None

Ethical Approval No ethical approval is needed to analyze and publish this public data. In addition, we have been granted by the Ministry of Health with access to surveillance data (SISPRO) which in addition is fully publicly available. 11

Conflicts of Interest: The authors have no conflict of interest to disclose.

Author contributions Study design: AJRM, UH, Data collection: CJGL, MLGM, JASR, SML, AFA, COLR, Data analysis: AJRM, UH, COLR, JDB, Writing: All authors. All authors read the final version submitted.

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References 1. Rodriguez-Morales AJ. Zika: the new arbovirus threat for Latin America. J Infect Dev Ctries. 2015; 9(6): 684-5. 2. Instituto Nacional de Salud de Bogotá. Zika a semana epidemiológica 11 de 2016. Instituto Nacional de Salud de Bogotá, 2016. URL: http://www.ins.gov.co/Noticias/ZIKA/Casos%20zika%20por%20municipio%20semana%2011%202016.pdf . Access date: March 19, 2016. 3. WHO. Zika situation report. Available at [ http://www.who.int/emergencies/zika-virus/situation-report/14-april- 2016/en/] , last visited 04.18.2016. 4. PAHO. Cumulative Zika suspected and confirmed cases reported by countries and territories in the Americas, 2015-2016. Updated as of 31 March 2016. URL: http://ais.paho.org/phip/viz/ed_zika_cases.asp . Access date: April 4, 2016. 5. Rodriguez-Morales AJ, Garcia-Loayza CJ, Galindo-Marquez ML, Sabogal-Roman JA, Marin-Loayza S, Lozada- Riascos CO, et al. Zika infection GIS-based mapping suggest high transmission activity in the border area of La Guajira, Colombia, a northeastern coast Caribbean department, 2015-2016: Implications for public health, migration and travel. Travel Med Infect Dis. 2016. 6. Rodriguez-Morales AJ, Galindo-Marquez ML, García-Loaiza CJ, Sabogal-Roman JA, Marin-Loaiza S, Ayala AF, Lozada-Riascos CO, Sarmiento-Ospina A, Vásquez-Serna H, Jimenez-Canizales CE, Escalera-Antezana JP. Mapping Zika virus infection using geographical information systems in Tolima, Colombia, 2015-2016 F1000Research 2016, 5:568. URL: http://dx.doi.org/10.12688/f1000research.8436.1 7. Valero N. Zika virus: Another emerging arbovirus in Venezuela? Invest Clin 2015;56:241 -2. 8. DIVA-GIS. Available at [ http://www.diva-gis.org/gdata] , last visited 04.09.2016. 9. Diaz-Quijano FA, Villar-Centeno LA, Martinez-Vega RA. Predictors of spontaneous bleeding in patients with acute febrile syndrome from a dengue endemic area. J Clin Virol. 2010; 49 (1):11-5. 10. Alvarado-Socarras JL, Ocampo-González M, Vargas-Soler JA, Rodriguez-Morales AJ, Franco-Paredes C. Congenital and Neonatal Chikungunya in Colombia. J Pediatric Infect Dis Soc. 2016 (accepted, in press # JPIDS- 2015-183.R2). 11. Rodriguez-Morales AJ. Zika and microcephaly in Latin America: An emerging threat for pregnant travelers? Travel Med Infect Dis. 2016; 14 (1): 5-6. 12. Musso D, Roche C, Robin E, Nhan T, Teissier A, Cao-Lormeau VM. Potential sexual transmission of Zika virus. Emerg Infect Dis. 2015; 21 (2): 359-61. 13. CDC. Zika and Blood Transfusion. Available at [http://www.cdc.gov/zika/transmission/blood-transfusion.html] , last visited 04.19.2016. 14. Rodriguez-Morales AJ, Bedoya-Arias JE, Ramírez-Jaramillo V, Montoya-Arias CP, Guerrero-Matituy EA, Cárdenas-Giraldo EV. Using Geographic information system (GIS) to mapping and assess changes in transmission patterns of chikungunya fever in municipalities of the Coffee-Triangle region of Colombia during 2014-2015 outbr eak: implications for travel advice. Travel Med Infect Dis 2016; 14:62 -5. 15. Rodriguez-Morales AJ, Cárdenas-Giraldo EV, Montoya-Arias CP, Guerrero-Matituy EA, Bedoya-Arias JE, Ramírez-Jaramillo V, Villamil-Gómez WE. Mapping chikungunya fever in municipalities of one coastal department of Colombia (Sucre) using Geographic information system (GIS) during 2014 outbreak: implications for travel advice. Travel Med Infect Dis 2015;13:256 -8.

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Supplement table 1. ZIKV incidence rates (cases/100,000pop) by municipalities in Norte de , Colombia, 2015-2016.

Municipalities Case Classification Total Population Total Incidence Rates RT-PCR Incidence Clinical Incidence RT-PCR Clinical Suspected Cases (2016) (cases/ 100,0000 pop) Rates (cases/ Rates (cases/ 100,0000 pop) 100,0000 pop) Santiago 2 127 0 129 2,844 4,535.86 70.32 4,465.54 Durania 1 62 0 63 3,735 1,686.75 26.77 1,659.97 Bochalema 0 0 83 83 7,020 1,182.34 0.00 0.00 Los patios 23 779 9 811 77,477 1,046.76 29.69 1,005.46 Salazar 0 0 87 87 8,942 972.94 0.00 0.00 54 169 0 223 23,107 965.08 233.70 731.38 Cucuta 564 5373 0 5937 656,414 904.46 85.92 818.54 Villa del Rosario 22 655 0 677 90,515 747.94 24.31 723.64 5 144 0 149 22,620 658.71 22.10 636.60 San Cayetano 1 34 0 35 5,537 632.11 18.06 614.05 0 0 53 53 8,972 590.73 0.00 0.00 Tibu 3 173 0 176 36,708 479.46 8.17 471.29 Chinacota 1 76 0 77 16,513 466.30 6.06 460.24 Puerto Santander 19 21 0 40 10,421 383.84 182.32 201.52 2 20 0 22 5,876 374.40 34.04 340.37 0 0 19 19 5,512 344.70 0.00 0.00 0 0 25 25 7,625 327.87 0.00 0.00 0 0 27 27 10,974 246.04 0.00 0.00 La playa 0 0 11 11 8,553 128.61 0.00 0.00 Ocaña 2 119 0 121 98,992 122.23 2.02 120.21 Lourdes 0 0 4 4 3,362 118.98 0.00 0.00 3 4 0 7 6,897 101.49 43.50 58.00 El Carmen 0 0 12 12 13,790 87.02 0.00 0.00 0 0 4 4 4,945 80.89 0.00 0.00 La esperanza 0 0 9 9 12,123 74.24 0.00 0.00 0 0 3 3 4,570 65.65 0.00 0.00 Abrego 1 20 0 21 38,363 54.74 2.61 52.13 Herran 1 1 0 2 4,006 49.93 24.96 24.96 Toledo 0 0 8 8 17,284 46.29 0.00 0.00 0 0 2 2 5,204 38.43 0.00 0.00 Cachira 0 0 3 3 11,008 27.25 0.00 0.00 0 0 4 4 21,978 18.20 0.00 0.00 0 0 2 2 13,631 14.67 0.00 0.00 Chitaga 0 0 1 1 10,391 9.62 0.00 0.00 Hacari 0 0 1 1 10,722 9.33 0.00 0.00 Convencion 0 0 1 1 13,296 7.52 0.00 0.00 Pamplona 2 0 2 4 57,803 6.92 3.46 0.00 Cacota 0 0 0 0 1,873 0.00 0.00 0.00 0 0 0 0 3,747 0.00 0.00 0.00 Silos 0 0 0 0 4,366 0.00 0.00 0.00 Unknown 1 0 19 20 - - - - municipality Whole N. 707 8,177 389 9,273 1,367,716 677.99 51.69 597.86 Santander 14

Supplement table 2. ZIKV incidence rates (cases/100,000pop) by municipalities in Santander department, Colombia, 2015-2016.

Municipalities Case Classification Total Cases Population Total Incidence RT-PCR Incidence Clinical Incidence (2016) Rates (cases/ Rates (cases/ Rates (cases/ RT-PCR Clinical Suspected 100,0000 pop) 100,0000 pop) 100,0000 pop) Capitanejo 0 0 137 137 5,543 2471.59 0.00 0.00 0 0 90 90 18,493 486.67 0.00 0.00 San Andrés 0 0 31 31 8,432 367.65 0.00 0.00 El Playón 0 0 39 39 11,646 334.88 0.00 0.00 San Miguel 0 0 4 4 2,349 170.29 0.00 0.00 1 283 0 284 191,704 148.15 0.52 147.62 Guadalupe 0 0 6 6 4,682 128.15 0.00 0.00 Bucaramanga 13 471 0 484 528,352 91.61 2.46 89.15 0 0 2 2 2,227 89.81 0.00 0.00 San Joaquin 0 0 2 2 2,445 81.80 0.00 0.00 Lebrija 6 23 0 29 39,398 73.61 15.23 58.38 Socorro 0 0 21 21 30,717 68.37 0.00 0.00 Floridablanca 3 166 0 169 266,102 63.51 1.13 62.38 Giron 0 0 112 112 185,248 60.46 0.00 0.00 0 0 4 4 7,166 55.82 0.00 0.00 Rionegro 0 0 14 14 26,896 52.05 0.00 0.00 Paramo 0 0 2 2 4,158 48.10 0.00 0.00 San Vicente de Chucuri 3 13 0 16 34,759 46.03 8.63 37.40 1 67 0 68 152,665 44.54 0.66 43.89 1 12 0 13 31,510 41.26 3.17 38.08 0 0 18 18 45,901 39.21 0.00 0.00 0 0 3 3 8,891 33.74 0.00 0.00 Jesus María 0 0 1 1 3,107 32.19 0.00 0.00 Guaca 0 0 2 2 6,345 31.52 0.00 0.00 Barbosa 2 7 0 9 28,873 31.17 6.93 24.24 Palmar 0 0 1 1 3,374 29.64 0.00 0.00 Gsepsa 0 0 1 1 3,804 26.29 0.00 0.00 0 0 2 2 7,688 26.01 0.00 0.00 San Benito 0 0 1 1 3,995 25.03 0.00 0.00 Valle de San José 0 0 1 1 4,607 21.71 0.00 0.00 Velez 0 0 4 4 18,993 21.06 0.00 0.00 La Paz 1 0 0 1 5,104 19.59 19.59 0.00 Concepción 0 0 1 1 5,230 19.12 0.00 0.00 Matanza 0 0 1 1 5,238 19.09 0.00 0.00 0 0 1 1 5,285 18.92 0.00 0.00 Los Santos 0 0 2 2 12,299 16.26 0.00 0.00 0 0 7 7 45,605 15.35 0.00 0.00 0 0 1 1 7,655 13.06 0.00 0.00 Sucre 0 0 1 1 8,324 12.01 0.00 0.00 La Belleza 0 0 1 1 8,592 11.64 0.00 0.00 Malaga 0 0 2 2 18,352 10.90 0.00 0.00 Suaita 0 0 1 1 10,212 9.79 0.00 0.00 Charala 0 0 1 1 10454 9.57 0.00 0.00 0 0 1 1 11,815 8.46 0.00 0.00 Curiti 0 0 1 1 11,942 8.37 0.00 0.00 Puente Nacional 0 0 1 1 12,270 8.15 0.00 0.00 Aguada 0 0 0 0 1,829 0.00 0.00 0.00 Albania 0 0 0 0 5,162 0.00 0.00 0.00 0 0 0 0 8,301 0.00 0.00 0.00 Betulia 0 0 0 0 5,075 0.00 0.00 0.00 Bolivar 0 0 0 0 12,204 0.00 0.00 0.00 Cabrera 0 0 0 0 2,313 0.00 0.00 0.00 California 0 0 0 0 2,006 0.00 0.00 0.00 Carcasi 0 0 0 0 5,021 0.00 0.00 0.00 Cepita 0 0 0 0 1,846 0.00 0.00 0.00 Cerrito 0 0 0 0 5,660 0.00 0.00 0.00 0 0 0 0 2,637 0.00 0.00 0.00 Chima 0 0 0 0 3,062 0.00 0.00 0.00 Chipata 0 0 0 0 5,080 0.00 0.00 0.00 15

Confines 0 0 0 0 2,697 0.00 0.00 0.00 Contratacion 0 0 0 0 3,451 0.00 0.00 0.00 0 0 0 0 7,584 0.00 0.00 0.00 El Carmen de Chucuri 0 0 0 0 20,296 0.00 0.00 0.00 0 0 0 0 1967 0.00 0.00 0.00 El Peñon 0 0 0 0 5,114 0.00 0.00 0.00 Encino 0 0 0 0 2,480 0.00 0.00 0.00 Enciso 0 0 0 0 3,258 0.00 0.00 0.00 Florian 0 0 0 0 6,293 0.00 0.00 0.00 Galan 0 0 0 0 2,244 0.00 0.00 0.00 Gambita 0 0 0 0 5,038 0.00 0.00 0.00 Guapota 0 0 0 0 2,120 0.00 0.00 0.00 Guavata 0 0 0 0 3,620 0.00 0.00 0.00 Hato 0 0 0 0 2,340 0.00 0.00 0.00 Jordan 0 0 0 0 1,099 0.00 0.00 0.00 Landazuri 0 0 0 0 15,395 0.00 0.00 0.00 0 0 0 0 2,336 0.00 0.00 0.00 0 0 0 0 10,885 0.00 0.00 0.00 0 0 0 0 5,130 0.00 0.00 0.00 0 0 0 0 4,748 0.00 0.00 0.00 0 0 0 0 5,003 0.00 0.00 0.00 San José de Miranda 0 0 0 0 4,303 0.00 0.00 0.00 Santa Bárbara 0 0 0 0 2,122 0.00 0.00 0.00 Santa Helena del Opon 0 0 0 0 4,288 0.00 0.00 0.00 Surata 0 0 0 0 3,264 0.00 0.00 0.00 Tona 0 0 0 0 7,129 0.00 0.00 0.00 0 0 0 0 2,444 0.00 0.00 0.00 Villanueva 0 0 0 0 5,753 0.00 0.00 0.00 Unknown municipality 0 0 3 3 - - - - Whole santander 31 1,042 523 1,596 2,071,044 77.06 1.50 50.31

*only municipalities reported cases are presented here.