• 1.

    WHO, 2018. Antimicrobial Resistance. Geneva, Switzerland: World Health Organization. Available at: http://www.who.int/mediacentre/factsheets/fs194/en/. Accessed May 9, 2017.

    • Search Google Scholar
    • Export Citation
  • 2.

    Okeke IN, Laxminarayan R, Bhutta ZA, Duse AG, Jenkins P, O’Brien TF, Pablos-Mendez A, Klugman KP, 2005. Antimicrobial resistance in developing countries. Part I: recent trends and current status. Lancet Infect Dis 5: 481493.

    • Search Google Scholar
    • Export Citation
  • 3.

    Wuijts S, van den Berg HH, Miller J, Abebe L, Sobsey M, Andremont A, Medlicott KO, van Passel MW, de Roda Husman AM, 2017. Towards a research agenda for water, sanitation and antimicrobial resistance. J Water Health 15: 175184.

    • Search Google Scholar
    • Export Citation
  • 4.

    Van Boeckel TP, Gandra S, Ashok A, Caudron Q, Grenfell BT, Levin SA, Laxminarayan R, 2014. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect Dis 14: 742750.

    • Search Google Scholar
    • Export Citation
  • 5.

    Van Boeckel TP, Brower C, Gilbert M, Grenfell BT, Levin SA, Robinson TP, Teillant A, Laxminarayan R, 2015. Global trends in antimicrobial use in food animals. Proc Natl Acad Sci USA 112: 56495654.

    • Search Google Scholar
    • Export Citation
  • 6.

    Ochoa TJ 2009. High frequency of antimicrobial drug resistance of diarrheagenic Escherichia coli in infants in Peru. Am J Trop Med Hyg 81: 296301.

    • Search Google Scholar
    • Export Citation
  • 7.

    Pehrsson EC 2016. Interconnected microbiomes and resistomes in low-income human habitats. Nature 533: 212216.

  • 8.

    Bartoloni A 2009. Antibiotic resistance in a very remote Amazonas community. Int J Antimicrob Agents 33: 125129.

  • 9.

    Pallecchi L 2012. Quinolone resistance in absence of selective pressure: the experience of a very remote community in the Amazon forest. PLoS Negl Trop Dis 6: e1790.

    • Search Google Scholar
    • Export Citation
  • 10.

    Dib JR, Weiss A, Neumann A, Ordoñez O, Estévez MC, Farías ME, 2009. Isolation of bacteria from remote high altitude Andean lakes able to grow in the presence of antibiotics. Recent Pat Antiinfect Drug Discov 4: 6676.

    • Search Google Scholar
    • Export Citation
  • 11.

    Lluque A, Mosquito S, Gomes C, Riveros M, Durand D, Tilley DH, Bernal M, Prada A, Ochoa TJ, Ruiz J, 2015. Virulence factors and mechanisms of antimicrobial resistance in Shigella strains from periurban areas of Lima (Peru). Int J Med Microbiol 305: 480490.

    • Search Google Scholar
    • Export Citation
  • 12.

    Kalter HD, Gilman RH, Moulton LH, Cullotta AR, Cabrera L, Velapatiño B, 2010. Risk factors for antibiotic-resistant Escherichia coli carriage in young children in Peru: community-based cross-sectional prevalence study. Am J Trop Med Hyg 82: 879888.

    • Search Google Scholar
    • Export Citation
  • 13.

    Kosek M, Yori PP, Pan WK, Olortegui MP, Gilman RH, Perez J, Chavez CB, Sanchez GM, Burga R, Hall E, 2008. Epidemiology of highly endemic multiply antibiotic-resistant shigellosis in children in the Peruvian Amazon. Pediatrics 122: e541e549.

    • Search Google Scholar
    • Export Citation
  • 14.

    WHO, 2015. Antimicrobial Resistance: Draft Global Action Plan on Antimicrobial Resistance. Sixty-Eighth World Health Assembly. Geneva, Switzerland: World Health Organization. Available at: http://apps.who.int/gb/ebwha/pdf_files/WHA68/A68_20-en.pdf?ua=1. Accessed November 24, 2017.

    • Search Google Scholar
    • Export Citation
  • 15.

    Hartinger SM, Lanata CF, Gil AI, Hattendorf J, Verastegui H, Mäusezahl D, 2012. Combining interventions: improved chimney stoves, kitchen sinks and solar disinfection of drinking water and kitchen clothes to improve home hygiene in rural Peru. Field Actions Science Reports: The Journal of Field Actions, Special Issue 6, 1–10. Available at: https://factsreports.revues.org/1627. Accessed November 28, 2017.

    • Search Google Scholar
    • Export Citation
  • 16.

    Hartinger SM, Nuño N, Hattendorf J, Verastegui H, Ortiz M, Mausezahl D, 2018. A factorial randomised controlled trial to combine home-environmental and early child development interventions to improve child health and development: rationale, trial design and baseline findings. Preprint BioRxiv, doi: 10.1101/465856.

  • 17.

    Rosa G, Huaylinos ML, Gil A, Lanata C, Clasen T, 2014. Assessing the consistency and microbiological effectiveness of household water treatment practices by urban and rural populations claiming to treat their water at home: a case study in Peru. PLoS One 9: e114997.

    • Search Google Scholar
    • Export Citation
  • 18.

    Mastroeni P, Carbone M, Fera MT, Teti G, 1983. Comparison of six systems for the identification of Enterobacteriaceae. G Batteriol Virol Immunol 76: 319.

    • Search Google Scholar
    • Export Citation
  • 19.

    Bauer AW, Kirby WM, Sherris JC, Turck M, 1966. Antibiotic susceptibility testing by a standardized single disk method. Am J Clin Pathol 45: 493496.

    • Search Google Scholar
    • Export Citation
  • 20.

    Clinical and Laboratory Standards Institute, 2017. M100: Performance Standards for Antimicrobial Susceptibility Testing. Wayne, PA: Clinical and Laboratory Standards Institute.

    • Search Google Scholar
    • Export Citation
  • 21.

    Lezameta L, Gonzáles-Escalante E, Tamariz JH, 2010. Comparison of four phenotypic methods to detect extended-spectrum betalactamases [article in Spanish]. Rev Peru Med Exp Salud Publica 27: 345351.

    • Search Google Scholar
    • Export Citation
  • 22.

    Guiral E, Pons MJ, Vubil D, Marí-Almirall M, Sigaúque B, Soto SM, Alonso PL, Ruiz J, Vila J, Mandomando I, 2018. Epidemiology and molecular characterization of multidrug-resistant Escherichia coli isolates harboring blaCTX-M group 1 extended-spectrum β-lactamases causing bacteremia and urinary tract infection in Manhiça, Mozambique. Infect Drug Resist 11: 927936.

    • Search Google Scholar
    • Export Citation
  • 23.

    R Core Team, 2017. R: A Language and Environment for Statistical Computing .Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

    • Search Google Scholar
    • Export Citation
  • 24.

    WHO, 2004. Guidelines for Drinking-Water Quality .Geneva, Switzerland: World Health Organization. Available at: http://www.who.int/water_sanitation_health/dwq/GDWQ2004web.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 25.

    Dirección General de Salud Ambiental Ministerio de Salud, 2011. Reglamento de La Calidad Del Agua Para Consumo Humano, Vol. DS N° 031-2010-SA. Peru: Ministerio de Salud (Ministry of Health). Available at: http://www.digesa.minsa.gob.pe/publicaciones/descargas/reglamento_calidad_agua.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 26.

    Ministerio de Salud (Ministry of Health) of Peru, 2015. Modifican Los Estándares Nacionales de Calidad Ambiental Para Agua y Establecen Disposiciones Complementarias Para Su Aplicación. Lima, Peru: El Peruano. Available at: http://www.minam.gob.pe/wp-content/uploads/2015/12/Decreto-Supremo-N%C2%B0-015-2015-MINAM.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bartoloni A 2006. Multidrug-resistant commensal Escherichia coli in children, Peru and Bolivia. Emerg Infect Dis 12: 907913.

  • 28.

    Pons MJ, Mosquito S, Gomes C, del Valle LJ, Ochoa TJ, Ruiz J, 2014. Analysis of quinolone-resistance in commensal and diarrheagenic Escherichia coli isolates from infants in Lima, Peru. Trans R Soc Trop Med Hyg 108: 2228.

    • Search Google Scholar
    • Export Citation
  • 29.

    Zhao W-H, Hu Z-Q, 2013. Epidemiology and genetics of CTX-M extended-spectrum β-lactamases in Gram-negative bacteria. Crit Rev Microbiol 39: 79101.

    • Search Google Scholar
    • Export Citation
  • 30.

    Pallecchi L, Bartoloni A, Fiorelli C, Mantella A, Di Maggio T, Gamboa H, Gotuzzo E, Kronvall G, Paradisi F, Rossolini GM, 2007. Rapid dissemination and diversity of CTX-M extended-spectrum β-lactamase genes in commensal Escherichia coli isolates from healthy children from low-resource settings in Latin America. Antimicrob Agents Chemother 51: 27202725.

    • Search Google Scholar
    • Export Citation
  • 31.

    Lukac PJ, Bonomo RA, Logan LK, 2015. Extended-spectrum β-lactamase–producing Enterobacteriaceae in children: old foe, emerging threat. Clin Infect Dis 60: 13891397.

    • Search Google Scholar
    • Export Citation
  • 32.

    Adrianzén D, Arbizu A, Ortiz J, Samalvides F, 2013. Mortality caused by bacteremia Escherichia coli and Klebsiella spp. extended-spectrum beta-lactamase- producers: a retrospective cohort from a hospital in Lima, Peru. Rev Peru Med Exp Salud Publica 30: 1825.

    • Search Google Scholar
    • Export Citation
  • 33.

    Aliaga FC, Andrade CS, Escalante EG, 2015. Enterobacterias productoras de betalactamasas de espectro extendido en muestras fecales en el Instituto Nacional de Salud del Niño, Perú. Revista Peruana de Medicina Exp y Salud Pública 32: 2632.

    • Search Google Scholar
    • Export Citation
  • 34.

    García C, Astocondor L, Rojo-Bezares B, Jacobs J, Sáenz Y, 2016. Molecular characterization of extended-spectrum β-lactamase-producer Klebsiella pneumoniae isolates causing neonatal sepsis in Peru. Am J Trop Med Hyg 94: 285288.

    • Search Google Scholar
    • Export Citation
  • 35.

    Korzeniewska E, Korzeniewska A, Harnisz M, 2013. Antibiotic resistant Escherichia coli in hospital and municipal sewage and their emission to the environment. Ecotoxicol Environ Saf 91 96102.

    • Search Google Scholar
    • Export Citation
  • 36.

    Dolejska M, Frolkova P, Florek M, Jamborova I, Purgertova M, Kutilova I, Cizek A, Guenther S, Literak I, 2011. CTX-M-15-producing Escherichia coli clone B2-O25b-ST131 and Klebsiella spp. isolates in municipal wastewater treatment plant effluents. J Antimicrob Chemother 66: 27842790.

    • Search Google Scholar
    • Export Citation
  • 37.

    De Boeck H, Miwanda B, Lunguya-Metila O, Muyembe-Tamfum J-J, Stobberingh E, Glupczynski Y, Jacobs J, 2012. ESBL-positive enterobacteria isolates in drinking water. Emerg Infect Dis 18: 10191020.

    • Search Google Scholar
    • Export Citation
  • 38.

    Abera B, Kibret M, Mulu W, 2016. Extended-spectrum beta (β)-lactamases and antibiogram in Enterobacteriaceae from clinical and drinking water sources from Bahir Dar city, Ethiopia. PLoS One 11: e0166519.

    • Search Google Scholar
    • Export Citation
  • 39.

    Madec J-Y, Haenni M, Ponsin C, Kieffer N, Rion E, Gassilloud B, 2016. Sequence type 48 Escherichia coli carrying the blaCTX-M-1 IncI1/ST3 plasmid in drinking water in France. Antimicrob Agents Chemother 60: 64306432.

    • Search Google Scholar
    • Export Citation
  • 40.

    Levy K, 2015. Does poor water quality cause diarrheal disease? Am J Trop Med Hyg 93: 899900.

  • 41.

    Clasen TF, Alexander KT, Sinclair D, Boisson S, Peletz R, Chang HH, Majorin F, Cairncross S, 2015. Interventions to improve water quality for preventing diarrhoea. Cochrane Database Syst Rev 10: CD004794.

    • Search Google Scholar
    • Export Citation
  • 42.

    Eisenberg JNS, Scott JC, Porco T, 2007. Integrating disease control strategies: balancing water sanitation and hygiene interventions to reduce diarrheal disease burden. Am J Public Health 97: 846852.

    • Search Google Scholar
    • Export Citation

 

 

 

 

 

Antibiotic-Resistant Escherichia coli in Drinking Water Samples from Rural Andean Households in Cajamarca, Peru

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  • 1 Facultad de Salud Publica y Adminstración, Universidad Peruana Cayetano Heredia, Lima, Peru;
  • 2 University of Washington, Seattle, Washington;
  • 3 Swiss Tropical and Public Health Institute, Basel, Switzerland;
  • 4 University of Basel, Basel, Switzerland

Antibiotic resistance in pathogenic bacteria is a serious public health issue. The growing threat is a cause for concern and action to prevent the emergence of new resistant strains and the spread of existing ones to humans via the environment. This study aimed at identifying fecal pathogens in drinking water obtained from rural Andean households from Cajamarca, Peru, and measuring the antibiotic resistance profile of Escherichia coli. The study was embedded within a community-randomized controlled trial among 102 communities in the northern highlands of the Cajamarca region, Peru. Of 314 samples, 55.4% (95% CI [49.7, 61.0], n = 174) were identified as thermotolerant coliforms. Among the samples positive for thermotolerant coliform, E. coli was isolated in 37.3% (n = 117), Klebsiella spp. in 8.0% (n = 25), Enterobacter spp. in 5.1% (n = 16), and Citrobacter spp. in 2.5% (n = 8). Of the 117 E. coli samples, 48.7% (95% CI [39.4, 58.1], n = 57) showed resistance to any antibiotic. The E. coli antibiotic resistance profile showed highest resistance against tetracycline (37.6%), ampicillin (34.2%), sulfamethoxazole–trimethoprim (21.4%), and nalidixic acid (13%). Some 19.7% (95% CI [12.9, 28.0], n = 23) of the E. coli isolates displayed multidrug resistance, defined as resistance to at least three classes of antibiotics. The CTX-M-3 gene, which encodes extended-spectrum resistance to beta-lactamase antibiotics, was found in one isolate. The high prevalence of fecal contamination in drinking water highlights the importance of household water treatment methods. Likewise, the high levels of antibiotic resistance found indicate a need for further research to identify the origins of potential environmental contamination, misuse, or inadequate disposal of antibiotics.

INTRODUCTION

Antibiotic resistance in pathogenic bacteria is a serious public health issue.1 The growing threat is a cause for concern and action to prevent the emergence of new resistant strains and the spread of existing ones from humans and animals in the environment.2 Although the use of antibiotics for treatment represents one of the most significant therapeutic advances in history, the appearance of antibiotic-resistant bacteria (ARB) now threatens our ability to manage common conditions, resulting in public health implications of longer illness durations, disability, and death.3 Global rates of antibiotic use in humans were estimated to increase by more than 30% in the first decade of the 21st century,4 with corresponding increases in worldwide antibiotic use in agriculture, the food industry, and aquaculture,5 facilitating the spread of antibiotic resistance genes by the release and accumulation of antibiotics in the entire human–animal–environment sphere.

Antibiotic resistance in wastewater, surface water, and drinking water is well documented.6,7 Animal and human fecal flora and the environment, including water sources, serve as natural habitats and reservoirs of antibiotic-resistant bacteria and resistance genes. A study investigating human fecal samples, household environmental samples including samples from household animals and household water samples, and wastewater treatment samples from a peri-urban area in Peru found links between the resistomes of bacteria of human, animal, and environmental origins.7 Within a community, resistant bacteria circulate among humans directly as well as between humans, animals, and the environment. The epidemiology of antibiotic-resistant microorganisms at the human–animal–environmental interface involves complex and largely unpredictable systems that include transmission routes of resistant bacteria, as well as resistance genes, and the impact of antibiotic-selective pressures in various reservoirs: animals, humans, and the environment.

Previous research in remote communities in Peru has illuminated the gaps in our understanding of environmental exposures to antibiotic resistance. The unexpected finding of carriage of antibiotic-resistant Escherichia coli among animals and humans in an isolated Amazonian community in Peru in the absence of high levels of antibiotic use represents a quintessential example of the complexity of antibiotic resistance transmission pathways.8,9 Research has found that remote, high-altitude Andean regions of South America harbor antibiotic-resistant bacteria in water bodies in the natural environment,10 but there are very little data addressing antibiotic-resistant bacteria in the immediate or household environment for remote, high-altitude Peruvian communities. Several studies have taken place in Peru regarding antibiotic resistance carriage and profile, but only one (Kalter et al.) included remote, high-altitude regions.6,7,1113 Kalter et al. investigated risk factors for antibiotic resistance among children in multiple regions of Peru and concluded that environmental contamination was as important as prior antibiotic use in increasing children’s carriage of antibiotic-resistant E. coli.12 As a result, there is a need for more targeted studies that assess household environmental exposure to ARB and risk factors that promote or favor ARB in rural and high-altitude areas of Peru.

In 2015, the WHO developed a Global Action Plan for Antimicrobial Resistance with the overarching goal of ensuring global access to safe and effective treatment for infectious diseases through strategies including research, surveillance, and infection reduction.14 A workshop on the WHO Action Plan held at the 2015 International Water Association Health-Related Water Microbiology Symposium was convened to focus on the issue of antimicrobial resistance in water, wastewater, and feces, addressing the role of water, sanitation, and hygiene. The primary conclusions of this workshop stipulated the need to further examine water and the environment as human exposure pathways for AMR, determine the health impact of AMR in water and compare it with other exposure routes, generate guidelines for intervention methods to reduce the spread of antimicrobial resistance (AMR) to humans via the environment, and finally, create a global surveillance system strategy that can be used in low-income countries to monitor the degree and the dissemination of AMR.3

In an effort to contribute to understanding of transmission pathways in the rural environment, our study aimed to identify the fecal pathogens in drinking water obtained from rural Andean households from Cajamarca, Peru, and to measure the antibiotic resistance profile and extended-spectrum beta-lactamase (ESBL) activity and genetic determinants in E. coli isolates in drinking water.

METHODOLOGY

Study setting.

The study was located in the provinces of San Marcos and Cajabamba, located in the northern Andean region of Peru (Department of Cajamarca), with altitudes between 2,200 and 3,900 m above sea level. Most of the population are small-scale farmers, living in houses with earthen floors, adobe walls, and clay tile roofs, and use unventilated traditional stoves or open fires for cooking.15 Water supply for homes in San Marcos and Cajabamba comes from a piped gravity system that transports untreated water captured from central community reservoirs or springs through individual or small-scale collective plastic piping to a tap in the courtyard.15

Study design.

The present study is embedded within an integrated community-randomized controlled trial (health and development effectiveness of an integrated home-based intervention package (IHIP-2) in rural Andean communities: a randomized trial (IHIP-2), registered at www.isrctn.com under ISRCTN-26548981), among 102 communities in the northern highlands of the Cajamarca Region, Peru. In brief, the IHIP-2 trial assessed the effectiveness of an integrated home-environmental intervention package comprising the installation of a kitchen sink with running water, ventilated improved cookstove and general kitchen, hand and food hygiene education, and early child development.16 For the parent study, participant families were eligible if they met the following criteria: 1) have at least one child aged < 1.5 months living at home, 2) use solid fuels as main energy source for cooking/heating, 3) have access to non-treated piped water in the yard or the community (15 m maximum), 4) do not plan to move within the next 24 months, and 5) are not participating in another program or intervention. All data presented here are from the baseline phase of the IHIP-2 trial.

Identification of fecal pathogens in drinking water.

Water sampling took place between October 2015 and January 2016. Field-workers visited each household and collected approximately 125 mL of water using sterile bottles (Labsystems S.A.C., Peru). Samples were obtained from the main source the child commonly used for drinking. If the researcher did not observe the drinking process, mothers were asked, “if your child was thirsty right now, what water would you give him to drink?” and a sample was collected from the indicated source. We performed socioeconomic surveys and collected water samples from a total of 314 households. Household surveys to collect socioeconomic data, which included water source and treatment, were collected between 0 and 190 days before the water sampling was performed, with a median difference of 65 days. The samples were transported from the field to the research station laboratory located in the city of San Marcos, using thermal bags with ice packs to conserve the samples. Training in the correct handling of the sample, transportation, and quantitative data collection was provided to the field-workers. The field supervisor reviewed all completed questionnaires on the day of collection.

Sample analysis.

We tested all samples within 8 hours after their collection. The water samples were analyzed for thermotolerant (fecal) coliforms using the membrane-filtration method of the Oxfam DelAgua Water Testing Kit (DelAgua, England), product code 14867. We incubated the samples at 44 ± 0.5°C, from 14 to 16 hours in lauryl sulfate broth. We read the samples according to the instructions of the kit, counting the yellow colony-forming units in the first 15 minutes, as indicative of thermotolerant bacterial growth. For further pathogen identification, five colonies per sample were saved in peptone media vials and were transported to the Enteric Diseases and Nutrition Laboratory at the Tropical Medicine Institute, Cayetano Heredia University, Lima, for analysis. Samples in which the coliform level was assigned too numerous to count were represented as 500 colonies for statistics and data analysis.17 Enterobacteriaceae isolates were identified using conventional media with standard methods.18

Antibiotic susceptibility testing.

The antibiotic resistance pattern was determined against 12 commonly used antibiotics using the Kirby–Bauer disk diffusion method according to the Clinical and Laboratory Standards Institute guidelines19,20: nalidixic acid (30-µg disk), chloramphenicol (30-µg disk), nitrofurantoin (300-µg disk), ciprofloxacin (5-µg disk), gentamicin (10-µg disk), tetracycline (30-µg disk), trimethoprim–sulfamethoxazole (25-µg disk), amoxicillin–clavulanic acid (30-µg disk), ampicillin (10-µg disk), cefotaxime (30-µg disk), azithromycin (15-µg disk), and cefoxitin (30-µg disk). Antibiotic susceptibility testing was performed for all isolated bacteria but is presented in aggregate only for E. coli because of low sample sizes in other bacteria.

Extended-spectrum beta-lactamases detection and confirmation.

Phenotypic detection of ESBL bacteria.

Antibiotic susceptibilities for all isolated strains of bacteria were tested using the Jarlier method21 for the following antibiotics: aztreonam (5-µg disk), ceftazidime (30-µg disk), cefotaxime (30-µg disk), ceftriaxone (30-µg disk), amoxicillin–clavulanic acid (30-µg disk), and cefepime (30-µg disk).

Molecular confirmation of ESBL genes.

Escherichia coli displaying phenotypic ESBL activity were tested for the presence of SHV, TEM, OXA-1-like, CTX-M-2, CTX-M-3, CTX-M-8, CTX-M-9, and CTX-M-10 genes using conventional polymerase chain reaction.22 Identified ESBL genes were not sequenced for allelic variants.

Data analysis.

Data were analyzed using STATA 14.0 (StataCorp., College Station, TX) and R version 3.5.1 (R Foundation for Statistical Computing, Austria).23 We present descriptive statistics and prevalence of coliform contamination and specific bacterial types. Using the binom.test() command in R, 95% CIs for prevalence of specific bacterial types and antibiotic resistance among E. coli isolates were calculated.

Ethics.

The project was registered on the ISRCTN registry (ISRCTN26548981). Community leaders and local authorities from the study signed a collaborative agreement with the Universidad Peruana Cayetano Heredia before study implementation. The parent participating in the study signed a written informed consent form.

RESULTS

Characteristics of study sample.

Almost all households providing water samples in this study have access to tap water piped into the home or building (99.4%). The gravity-based piped water supply system provides water to each household. However, this water is untreated and chlorination is uncommon. Drinking water at home is typically either consumed directly without treatment (40.8%) or boiled (57.6%) among households providing water samples this study, with a small minority (1.6%) treating water with chlorine or bleach.

Bacterial contamination of water sources.

Of 314 samples collected, 55.4% (n = 174) were positive for thermotolerant coliforms (Table 2); 35.0% (n = 110) of samples had more than 20 colonies. We classified the type of bacteria (E. coli, Enterobacter, Klebsiella, Citrobacter, or a non-fermenter) in 144 of these samples. We isolated multiple distinct species of thermotolerant bacteria in 7.3% of the 314 samples. Samples were provided from different water sources or containers depending on the household. Escherichia coli was isolated in 37.3% (n = 117) of all households, Klebsiella spp. in 8.0% (n = 25), Enterobacter spp. in 5.1% (n = 16), and Citrobacter spp. in 2.5% (n = 8) (Table 2). Of the 314 households tested for fecal coliforms, 280 (89.2%) reported using the same container in which the sample was collected to give water to children in the household, including 156 of the households in which thermotolerant fecal coliforms were isolated.

Table 1

Descriptive statistics of household water supply and treatment

Household water sourcesHouseholds, % (N)
Public system/piped water—inside the home or building99.3% (304)
Other/surface water0.65% (2)
Water treatment
 Boiling57.2% (175)
 Chlorine or bleach1.63% (5)
 None*41.1% (126)

* One hundred twenty-seven households reported no water treatment, but one subsequently reported use of boiling.

Table 2

Descriptive statistics of bacterial contamination by colony-forming units (CFU/mL), frequency, and type of thermotolerant coliform identified

Coliform levels
 Thermotolerant coliform count (CFU/mL)—median (IQR 1st–3rd Quantile)2 (0–85)
 Thermotolerant coliform count (CFU/mL)—mean (SD)100.0 (177.9)
Bacterial typesHouseholds, % (95% CI) N
 Thermotolerant coliform (any level)55.4% (49.7,61.0) 174
Escherichia coli37.3% (31.9, 42.9) 117
Klebsiella8.0% (5.2, 11.5) 25
Enterobacter5.1% (95% CI: 2.9, 8.1) 16
Citrobacter2.5% (95% CI: 1.1, 5.0) 8

Antibiotic resistance of bacterial isolates.

Of 117 E. coli samples (one per household), 48.7% displayed resistance to at least one antibiotic (Table 3). The E. coli antibiotic resistance profile showed highest resistance against tetracycline (32.5%), followed by ampicillin (28.2%), trimethoprim–sulfamethoxazole (17.9%), and nalidixic acid (9.4%) (Table 3). Multidrug resistance was displayed in 19.7% (23) of the E. coli isolates from this study (Table 3). Multidrug resistance was defined as resistance to three or more of the following classes of antibiotics: penicillins, quinolones, nitrofurans, aminoglycosides, tetracyclines, folate inhibitors, cephalosporins, macrolides, and phenicols.

Table 3

Escherichia coli antibiotic resistance profile to a panel of antibiotics, proportion of isolates resistant to any antibiotic, and proportion of multidrug-resistant isolates, where multidrug resistance was defined as resistance to three or more classes of antibiotics

AntibioticSusceptible, % (N)Intermediate, % (N)Resistant, % (N)% Resistant (95% CI)
Amoxicillin–clavulanic acid90.6% (106)6.0% (7)3.4% (4)(0.94, 8.5)
Ampicillin48.7% (57)23.1% (27)28.2% (33)(20.3, 37.3)
Azithromycin93.2% (109)6.8% (8)(3.0, 13.0)
Cefotaxime94.9% (111)1.7% (2)3.4% (4)(0.94, 8.5)
Cefoxitin96.8% (30)3.2% (1)(0.08, 16.7)
Chloramphenicol88.9% (104)0.0% (0)11.1% (13)(6.1, 18.3)
Ciprofloxacin90.6% (106)5.1% (6)4.3% (5)(1.4, 9.7)
Gentamicin97.4% (114)2.6% (3)(0.53, 7.3)
Nalidixic acid85.5% (100)5.1% (6)9.4% (11)(4.8, 16.2)
Nitrofurantoin94.9% (111)3.4% (4)1.7% (2)(0.21, 6.0)
Trimethoprim–sulfamethoxazole81.2% (95)0.9% (1)17.9% (21)(11.5, 26.1)
Tetracycline67.5% (79)32.5% (38)(24.1, 41.8)
Any antibiotic48.7% (57)(39.4, 58.1)
Multidrug resistance19.7% (23)(12.9, 28.0)

Detection of ESBL resistance genes.

Eight strains of bacteria, including six E. coli and two Klebsiella isolates, displayed phenotypic ESBL activity. One isolate was found to carry the CTX-M-3 gene. All of the other strains displaying phenotypic ESBL activity were found to be negative for carriage of all tested ESBL genes.

DISCUSSION

This study was among the first to examine environmental contamination with antibiotic-resistant bacteria in remote Andean regions of Peru. The findings of thermotolerant coliform in the drinking water given to children in a majority of households and widespread antibiotic resistance among water contamination suggest that drinking water represents a potential transmission route for carriage and infection with ARB.

The high prevalence of fecal contamination indicates that lack of access to safe drinking water is an area of concern for the households in the region under study. A majority of the households in this study (55.4%) contained thermotolerant coliforms, indicating fecal contamination.24 Both Peruvian national standards for drinking water and the WHO guidelines indicate that no fecal or thermotolerant fecal coliforms should be detectable in a treated drinking water sample (the WHO specifies a 100-mL sample).24,25 Many households in this study (35.0%) were also found to have thermotolerant coliform levels in drinking water samples in excess of Peruvian legal standards for water that could be made potable for disinfection.26 These results indicate that research and interventions to address water contamination in this setting cannot rely solely on household and community disinfection measures, and should also identify and target sources of water contamination.

The finding of resistance to at least one antibiotic in more than half (51%) of E. coli isolates from drinking water indicates a potentially important role for drinking water in contributing to the carriage of antibiotic-resistant E. coli among rural communities in Peru. Antibiotic resistance in E. coli was most commonly identified among older generations of antibiotics, foremost in tetracycline (35.0%), ampicillin (30.5%), trimethoprim–sulfamethoxazole (20.7%), and chloramphenicol (11.9%). These results are consistent with studies of E. coli in fecal samples of children6,9,12,27 and adults9 in other areas of Peru, where resistance to tetracycline, ampicillin, trimethoprim–sulfamethoxazole, and chloramphenicol are consistently among the most commonly identified resistance phenotypes. Previous studies in Peru have explored the relationship between fecal carriage of antibiotic-resistant bacteria in humans and environmental and animal sources of bacteria in Peru,7,9,12 and suggested that the source and storage of drinking water may play an important role in antibiotic-resistant infections.13 The present study provides direct evidence that antibiotic-resistant bacteria are present in drinking water and will enable the evaluation of household risk factors, including animals and water storage, in future analyses.

The finding of moderate resistance to the quinolone antibiotics nalidixic acid (12.9%) and ciprofloxacin (5.9%), in particular, among drinking water bacteria, may contribute to explaining the phenomenon of unexpectedly high quinolone resistance in populations with limited exposure to this class of antibiotics. In previous studies by Bartoloni and others,9 a rapid increase in quinolone resistance was observed in a remote community in the Peruvian Amazon following a rise in quinolone use in other areas of Peru despite the absence of antibiotic selection pressure within that community. In addition, previous studies have noted a high prevalence of resistance to nalidixic acid among E. coli isolates in young children in Peru (28% to diarrheagenic E. coli and 32% to commensal strains), despite quinolone antibiotics not being historically recommended for pediatric use.28 Drinking water may represent one mechanism of transmission of quinolone resistance carriage to children and populations that are not expected to be exposed to high levels of quinolone use.

Eight isolates of bacteria showed phenotypic indications of ESBL resistance and one E. coli isolate was found to carry the CTX-M-3 gene, a relatively rare variant of the CTX-M type of beta-lactamase genes.29 Beta-lactam antibiotics are a class of antibiotics that are valuable and widely used in human and veterinary medicine alike. Bacteria carrying CTX-M genes for ESBL production are known agents of nosocomial and community infections and have been identified across human, animal, and environmental sources.30 They pose a particular threat to children, given that antibiotic treatment options for infections in children are limited,31 and it is critically important to preserve the efficacy of those that exist, such as cephalosporins. Escherichia coli with resistance to extended-spectrum cephalosporins were recently shown to be rapidly increasing in fecal carriage by Peruvian children, and this trend is highly related to the spread of CTX-M–type ESBL genes.30 Extended-spectrum beta-lactamase–producing Enterobacteriaceae, including CTX-M producers among others, have been identified as frequent agents of bacteremia among patients in Peruvian hospitals,3234 and the presence of ESBL production is associated with higher mortality in cases of bacteremia.32 Previous studies have demonstrated that ESBL-producing bacteria can be found worldwide in environmental water reservoirs, such as in hospital and municipal sewage and wastewater, including posttreatment waters.35,36 There is evidence of the presence of ESBL-producing bacteria in drinking water in both low- and high-income countries worldwide.3739 The presence of a strain of ESBL-producing bacteria in the present study suggests that drinking water may serve as a route of transmission and potential source of community-acquired infections with ESBL-producing Enterobacteriaceae.

Drinking water contamination presents a risk for enteric disease, and the prevalence of thermotolerant bacteria identified in the present study indicates the need for research into waterborne illness and interventions to improve water quality among the study community. Interventions to improve water quality are associated with reductions in diarrheal disease.40,41 Previous research in rural Peru found that both using an improved water source and water storage in a container with a properly fitted lid were protective factors against shigellosis infection in children.13 However, it is important to note that the bacterial contamination identified in the present study is not necessary directly associated with illness. Although some previous studies found an association between bacterial contamination of drinking water and diarrheal disease incidence,42 studies using coliform levels or E. coli to assess water quality show considerable heterogeneity.40 The relationship between thermotolerant coliforms or even specific indicator bacteria and illness is complex, where illness outcomes of interest may be caused by multiple pathogens from various exposure routes.40

The prevalence of bacterial contamination and antibiotic resistance described here among household water sources given to children aged 5 years and younger emphasizes the need for comprehensive research into causes and prevention strategies for contamination of drinking water. In particular, it will be important to explore the transmission pathway for bacteria, especially antibiotic-resistant bacteria, from the source to the point of exposure and evaluate the extent to which drinking water directly contributes to carriage and infection with antibiotic-resistant bacteria. Further analyses should directly investigate sources and risk factors for drinking water contamination with ARB and quantify the relationship between drinking water contamination and illness in remote, high-altitude settings.

Acknowledgments:

We wish to express our appreciation and thank the study families for their kind participation and the local authorities for their continuous support. We also express our gratitude to the field coordinators, especially to Angelica Fernandez, for their hard work and perseverance.

REFERENCES

  • 1.

    WHO, 2018. Antimicrobial Resistance. Geneva, Switzerland: World Health Organization. Available at: http://www.who.int/mediacentre/factsheets/fs194/en/. Accessed May 9, 2017.

    • Search Google Scholar
    • Export Citation
  • 2.

    Okeke IN, Laxminarayan R, Bhutta ZA, Duse AG, Jenkins P, O’Brien TF, Pablos-Mendez A, Klugman KP, 2005. Antimicrobial resistance in developing countries. Part I: recent trends and current status. Lancet Infect Dis 5: 481493.

    • Search Google Scholar
    • Export Citation
  • 3.

    Wuijts S, van den Berg HH, Miller J, Abebe L, Sobsey M, Andremont A, Medlicott KO, van Passel MW, de Roda Husman AM, 2017. Towards a research agenda for water, sanitation and antimicrobial resistance. J Water Health 15: 175184.

    • Search Google Scholar
    • Export Citation
  • 4.

    Van Boeckel TP, Gandra S, Ashok A, Caudron Q, Grenfell BT, Levin SA, Laxminarayan R, 2014. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect Dis 14: 742750.

    • Search Google Scholar
    • Export Citation
  • 5.

    Van Boeckel TP, Brower C, Gilbert M, Grenfell BT, Levin SA, Robinson TP, Teillant A, Laxminarayan R, 2015. Global trends in antimicrobial use in food animals. Proc Natl Acad Sci USA 112: 56495654.

    • Search Google Scholar
    • Export Citation
  • 6.

    Ochoa TJ 2009. High frequency of antimicrobial drug resistance of diarrheagenic Escherichia coli in infants in Peru. Am J Trop Med Hyg 81: 296301.

    • Search Google Scholar
    • Export Citation
  • 7.

    Pehrsson EC 2016. Interconnected microbiomes and resistomes in low-income human habitats. Nature 533: 212216.

  • 8.

    Bartoloni A 2009. Antibiotic resistance in a very remote Amazonas community. Int J Antimicrob Agents 33: 125129.

  • 9.

    Pallecchi L 2012. Quinolone resistance in absence of selective pressure: the experience of a very remote community in the Amazon forest. PLoS Negl Trop Dis 6: e1790.

    • Search Google Scholar
    • Export Citation
  • 10.

    Dib JR, Weiss A, Neumann A, Ordoñez O, Estévez MC, Farías ME, 2009. Isolation of bacteria from remote high altitude Andean lakes able to grow in the presence of antibiotics. Recent Pat Antiinfect Drug Discov 4: 6676.

    • Search Google Scholar
    • Export Citation
  • 11.

    Lluque A, Mosquito S, Gomes C, Riveros M, Durand D, Tilley DH, Bernal M, Prada A, Ochoa TJ, Ruiz J, 2015. Virulence factors and mechanisms of antimicrobial resistance in Shigella strains from periurban areas of Lima (Peru). Int J Med Microbiol 305: 480490.

    • Search Google Scholar
    • Export Citation
  • 12.

    Kalter HD, Gilman RH, Moulton LH, Cullotta AR, Cabrera L, Velapatiño B, 2010. Risk factors for antibiotic-resistant Escherichia coli carriage in young children in Peru: community-based cross-sectional prevalence study. Am J Trop Med Hyg 82: 879888.

    • Search Google Scholar
    • Export Citation
  • 13.

    Kosek M, Yori PP, Pan WK, Olortegui MP, Gilman RH, Perez J, Chavez CB, Sanchez GM, Burga R, Hall E, 2008. Epidemiology of highly endemic multiply antibiotic-resistant shigellosis in children in the Peruvian Amazon. Pediatrics 122: e541e549.

    • Search Google Scholar
    • Export Citation
  • 14.

    WHO, 2015. Antimicrobial Resistance: Draft Global Action Plan on Antimicrobial Resistance. Sixty-Eighth World Health Assembly. Geneva, Switzerland: World Health Organization. Available at: http://apps.who.int/gb/ebwha/pdf_files/WHA68/A68_20-en.pdf?ua=1. Accessed November 24, 2017.

    • Search Google Scholar
    • Export Citation
  • 15.

    Hartinger SM, Lanata CF, Gil AI, Hattendorf J, Verastegui H, Mäusezahl D, 2012. Combining interventions: improved chimney stoves, kitchen sinks and solar disinfection of drinking water and kitchen clothes to improve home hygiene in rural Peru. Field Actions Science Reports: The Journal of Field Actions, Special Issue 6, 1–10. Available at: https://factsreports.revues.org/1627. Accessed November 28, 2017.

    • Search Google Scholar
    • Export Citation
  • 16.

    Hartinger SM, Nuño N, Hattendorf J, Verastegui H, Ortiz M, Mausezahl D, 2018. A factorial randomised controlled trial to combine home-environmental and early child development interventions to improve child health and development: rationale, trial design and baseline findings. Preprint BioRxiv, doi: 10.1101/465856.

  • 17.

    Rosa G, Huaylinos ML, Gil A, Lanata C, Clasen T, 2014. Assessing the consistency and microbiological effectiveness of household water treatment practices by urban and rural populations claiming to treat their water at home: a case study in Peru. PLoS One 9: e114997.

    • Search Google Scholar
    • Export Citation
  • 18.

    Mastroeni P, Carbone M, Fera MT, Teti G, 1983. Comparison of six systems for the identification of Enterobacteriaceae. G Batteriol Virol Immunol 76: 319.

    • Search Google Scholar
    • Export Citation
  • 19.

    Bauer AW, Kirby WM, Sherris JC, Turck M, 1966. Antibiotic susceptibility testing by a standardized single disk method. Am J Clin Pathol 45: 493496.

    • Search Google Scholar
    • Export Citation
  • 20.

    Clinical and Laboratory Standards Institute, 2017. M100: Performance Standards for Antimicrobial Susceptibility Testing. Wayne, PA: Clinical and Laboratory Standards Institute.

    • Search Google Scholar
    • Export Citation
  • 21.

    Lezameta L, Gonzáles-Escalante E, Tamariz JH, 2010. Comparison of four phenotypic methods to detect extended-spectrum betalactamases [article in Spanish]. Rev Peru Med Exp Salud Publica 27: 345351.

    • Search Google Scholar
    • Export Citation
  • 22.

    Guiral E, Pons MJ, Vubil D, Marí-Almirall M, Sigaúque B, Soto SM, Alonso PL, Ruiz J, Vila J, Mandomando I, 2018. Epidemiology and molecular characterization of multidrug-resistant Escherichia coli isolates harboring blaCTX-M group 1 extended-spectrum β-lactamases causing bacteremia and urinary tract infection in Manhiça, Mozambique. Infect Drug Resist 11: 927936.

    • Search Google Scholar
    • Export Citation
  • 23.

    R Core Team, 2017. R: A Language and Environment for Statistical Computing .Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

    • Search Google Scholar
    • Export Citation
  • 24.

    WHO, 2004. Guidelines for Drinking-Water Quality .Geneva, Switzerland: World Health Organization. Available at: http://www.who.int/water_sanitation_health/dwq/GDWQ2004web.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 25.

    Dirección General de Salud Ambiental Ministerio de Salud, 2011. Reglamento de La Calidad Del Agua Para Consumo Humano, Vol. DS N° 031-2010-SA. Peru: Ministerio de Salud (Ministry of Health). Available at: http://www.digesa.minsa.gob.pe/publicaciones/descargas/reglamento_calidad_agua.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 26.

    Ministerio de Salud (Ministry of Health) of Peru, 2015. Modifican Los Estándares Nacionales de Calidad Ambiental Para Agua y Establecen Disposiciones Complementarias Para Su Aplicación. Lima, Peru: El Peruano. Available at: http://www.minam.gob.pe/wp-content/uploads/2015/12/Decreto-Supremo-N%C2%B0-015-2015-MINAM.pdf. Accessed September 26, 2017.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bartoloni A 2006. Multidrug-resistant commensal Escherichia coli in children, Peru and Bolivia. Emerg Infect Dis 12: 907913.

  • 28.

    Pons MJ, Mosquito S, Gomes C, del Valle LJ, Ochoa TJ, Ruiz J, 2014. Analysis of quinolone-resistance in commensal and diarrheagenic Escherichia coli isolates from infants in Lima, Peru. Trans R Soc Trop Med Hyg 108: 2228.

    • Search Google Scholar
    • Export Citation
  • 29.

    Zhao W-H, Hu Z-Q, 2013. Epidemiology and genetics of CTX-M extended-spectrum β-lactamases in Gram-negative bacteria. Crit Rev Microbiol 39: 79101.

    • Search Google Scholar
    • Export Citation
  • 30.

    Pallecchi L, Bartoloni A, Fiorelli C, Mantella A, Di Maggio T, Gamboa H, Gotuzzo E, Kronvall G, Paradisi F, Rossolini GM, 2007. Rapid dissemination and diversity of CTX-M extended-spectrum β-lactamase genes in commensal Escherichia coli isolates from healthy children from low-resource settings in Latin America. Antimicrob Agents Chemother 51: 27202725.

    • Search Google Scholar
    • Export Citation
  • 31.

    Lukac PJ, Bonomo RA, Logan LK, 2015. Extended-spectrum β-lactamase–producing Enterobacteriaceae in children: old foe, emerging threat. Clin Infect Dis 60: 13891397.

    • Search Google Scholar
    • Export Citation
  • 32.

    Adrianzén D, Arbizu A, Ortiz J, Samalvides F, 2013. Mortality caused by bacteremia Escherichia coli and Klebsiella spp. extended-spectrum beta-lactamase- producers: a retrospective cohort from a hospital in Lima, Peru. Rev Peru Med Exp Salud Publica 30: 1825.

    • Search Google Scholar
    • Export Citation
  • 33.

    Aliaga FC, Andrade CS, Escalante EG, 2015. Enterobacterias productoras de betalactamasas de espectro extendido en muestras fecales en el Instituto Nacional de Salud del Niño, Perú. Revista Peruana de Medicina Exp y Salud Pública 32: 2632.

    • Search Google Scholar
    • Export Citation
  • 34.

    García C, Astocondor L, Rojo-Bezares B, Jacobs J, Sáenz Y, 2016. Molecular characterization of extended-spectrum β-lactamase-producer Klebsiella pneumoniae isolates causing neonatal sepsis in Peru. Am J Trop Med Hyg 94: 285288.

    • Search Google Scholar
    • Export Citation
  • 35.

    Korzeniewska E, Korzeniewska A, Harnisz M, 2013. Antibiotic resistant Escherichia coli in hospital and municipal sewage and their emission to the environment. Ecotoxicol Environ Saf 91 96102.

    • Search Google Scholar
    • Export Citation
  • 36.

    Dolejska M, Frolkova P, Florek M, Jamborova I, Purgertova M, Kutilova I, Cizek A, Guenther S, Literak I, 2011. CTX-M-15-producing Escherichia coli clone B2-O25b-ST131 and Klebsiella spp. isolates in municipal wastewater treatment plant effluents. J Antimicrob Chemother 66: 27842790.

    • Search Google Scholar
    • Export Citation
  • 37.

    De Boeck H, Miwanda B, Lunguya-Metila O, Muyembe-Tamfum J-J, Stobberingh E, Glupczynski Y, Jacobs J, 2012. ESBL-positive enterobacteria isolates in drinking water. Emerg Infect Dis 18: 10191020.

    • Search Google Scholar
    • Export Citation
  • 38.

    Abera B, Kibret M, Mulu W, 2016. Extended-spectrum beta (β)-lactamases and antibiogram in Enterobacteriaceae from clinical and drinking water sources from Bahir Dar city, Ethiopia. PLoS One 11: e0166519.

    • Search Google Scholar
    • Export Citation
  • 39.

    Madec J-Y, Haenni M, Ponsin C, Kieffer N, Rion E, Gassilloud B, 2016. Sequence type 48 Escherichia coli carrying the blaCTX-M-1 IncI1/ST3 plasmid in drinking water in France. Antimicrob Agents Chemother 60: 64306432.

    • Search Google Scholar
    • Export Citation
  • 40.

    Levy K, 2015. Does poor water quality cause diarrheal disease? Am J Trop Med Hyg 93: 899900.

  • 41.

    Clasen TF, Alexander KT, Sinclair D, Boisson S, Peletz R, Chang HH, Majorin F, Cairncross S, 2015. Interventions to improve water quality for preventing diarrhoea. Cochrane Database Syst Rev 10: CD004794.

    • Search Google Scholar
    • Export Citation
  • 42.

    Eisenberg JNS, Scott JC, Porco T, 2007. Integrating disease control strategies: balancing water sanitation and hygiene interventions to reduce diarrheal disease burden. Am J Public Health 97: 846852.

    • Search Google Scholar
    • Export Citation

Author Notes

Address correspondence to Stella Maria Hartinger, Universidad Peruana Cayetano Heredia, Av. Honorio Delgado 430, Urb. Ingeniería SMP, Lima 15102, Peru. E-mail: stella.hartinger.p@upch.pe

Financial support: This study received financial support from the UBS Optimus Foundation and the Grand Challenges Canada, through a grant given to the UPCH and the Swiss Tropical and Public Health Institute (Swiss TPH). The sponsors had no involvement in the study design, data collection and analysis, writing, or the decision to submit the article for publication. In addition, research reported in this publication was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW009375. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Authors’ addresses: Anika Larson, Hector Verastegui, and Maria Luisa Huaylinos, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru, E-mails: larsona@uw.edu, hector.verastegui.h@upch.pe, and maria.huaylinos.b@upch.pe. Stella Maria Hartinger, Unidad de Desarrollo Integral, Ambiente y Salud, Facultad de Salud Publica y Administracion, Universidad Peruana Cayetano Heredia, Lima, Peru, and Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland, E-mail: stella.hartinger.p@upch.pe. Maribel Riveros, Instituto de Medicina Tropical, Universidad Peruana Cayetano Heredia, Lima, Peru, E-mail: maribel.riveros@upch.pe. Gabriela Salmon-Mulanovich, Departamento de Ingeniería, Pontificia Universidad Catolica del Peru, Lima, Peru, E-mail: gsalmonm@pucp.edu.pe. Jan Hattendorf and Daniel Mäusezahl, Department of Epidemiology and Public Health, Schweizerisches Tropen- und Public Health-Institut, Basel, Switzerland, E-mails: jan.hattendorf@swisstph.ch and daniel.maeusezahl@swisstph.ch.

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