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Epidemiological study of prevalent pathogens in the Northwest region of Argentina (NWA)

  • Mónica Florencia Torrez Lamberti,

    Roles Data curation, Formal analysis, Methodology, Writing – original draft

    Affiliation Instituto Superior de Investigaciones Biológicas (INSIBIO), CONICET-UNT, and Instituto de Química Biológica “Dr. Bernabé Bloj”, Facultad de Bioquímica, Química y Farmacia, UNT, San Miguel de Tucumán, Argentina

  • Fabián Enrique López,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Validation

    Affiliation Instituto Superior de Investigaciones Biológicas (INSIBIO), CONICET-UNT, and Instituto de Química Biológica “Dr. Bernabé Bloj”, Facultad de Bioquímica, Química y Farmacia, UNT, San Miguel de Tucumán, Argentina

  • Patricia Valdez,

    Roles Data curation, Investigation, Resources

    Affiliation Hospital Interzonal de Niños Eva Perón (HINEP), San Fernando del Valle de Catamarca, Catamarca, Argentina

  • Ana Bianchi,

    Roles Data curation, Investigation, Resources

    Affiliation Centro Provincial de Salud Infantil “Eva Perón” (CePSI), Santiago del Estero, Argentina

  • Evangelina Barrionuevo Medina,

    Roles Data curation, Investigation, Resources

    Affiliation Hospital del Niño Jesús (HNJ), San Miguel de Tucumán, Tucumán, Argentina

  • María de las Mercedes Pescaretti ,

    Roles Conceptualization, Data curation, Funding acquisition, Investigation, Supervision, Writing – original draft

    monica.delgado@fbqf.unt.edu.ar (MAD); mpescaretti@fbqf.unt.edu.ar (MMP)

    Affiliation Instituto Superior de Investigaciones Biológicas (INSIBIO), CONICET-UNT, and Instituto de Química Biológica “Dr. Bernabé Bloj”, Facultad de Bioquímica, Química y Farmacia, UNT, San Miguel de Tucumán, Argentina

  • Mónica Alejandra Delgado

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft

    monica.delgado@fbqf.unt.edu.ar (MAD); mpescaretti@fbqf.unt.edu.ar (MMP)

    Affiliation Instituto Superior de Investigaciones Biológicas (INSIBIO), CONICET-UNT, and Instituto de Química Biológica “Dr. Bernabé Bloj”, Facultad de Bioquímica, Química y Farmacia, UNT, San Miguel de Tucumán, Argentina

Abstract

Northwest Argentina (NWA) is a poor economic-geographical region, with the highest rate of diarrhea diseases. At the moment, there are no reports showing the epidemiological status of this region that would allow to establish methods for prevention and control of these infections and to indicate of the prevalent pathogen that produces them. Therefore we carried out an epidemiological study of the gastroenteritis etiological agents and their incidence in the pediatric population. A total of 17 823 fecal samples were collected, 14 242 from HNJ-Tuc, 2,257 from CePSI-Stgo and 1,324 from HINEP-Cat. In 2,595 samples a bacterial agent was identified, the 93.64% corresponded to Shigella/Salmonella clinical isolates. Shigella genus was the prevalent pathogen, being Shigella flexneri 2 the most frequent serotype. Most of the Shigella clinical isolates presented themselves as multidrug-resistant (MDR), harboring 2 to 3 genetic resistance determinants. 50% of the affected patients were children under 4 years old. Here, we demonstrate that bacterial gastrointestinal diseases strongly affect the health of NWA population. The appearance of epidemic outbreaks, as happened during 2014, suggest that they may be related to the socio-economic poverty of NWA. Recently, Shigella flexneri 2 has become the highest NWA´s incidence infectious agent. The acquisition of new antibiotic resistance determinants may play an important role in their adaptation and persistence.

Introduction

Infectious diseases causing diarrhea are among the major cause of morbidity and mortality in children under 5 years old [13]. Foodborne Diseases (FBD) are transmitted by consumption of contaminated food. Escherichia coli (E. coli), Salmonella, and Shigella are the principal cause of most of the worldwide foodborne outbreaks [47].

According to the World Health Organization in America around 77 000 000 people are affected by FBD, causing about 2,000 deaths of children under 5 years old per year [8, 9]. In Argentina shigellosis is one of the main causes of children’s morbidity and mortality, where around 1 200 000 cases of acute diarrhea in public hospitals are being reported per year [10]. NWA is an economic-geographical region that involves 6 of the 23 provinces that establish the Argentine territory [11]. The acute diarrhea cases of NWA represent the 30% of the total Argentina’s cases [10].

In Argentina, Shigella is the major causative agent of diarrhea, followed by Salmonella and E. coli strains [1214]. The aim of this work was to conduct the first epidemiologic study of bacterial pathogens causing gastrointestinal disease, determining the incidence of Salmonella and Shigella in the pediatric population of three provinces of NWA.

Materials and methods

Study area and period

In this study we collaborated with the hospital from Catamarca (Hospital Interzonal del Niño "Eva Perón", HINEP), Santiago del Estero (Centro Provincial de Salud Infantil "Eva Perón", CePSI) and Tucumán (Hospital del Niño Jesus, HNJ). These hospitals are the central emergency department responsible for receiving and processing most fecal samples (Fs) from patients suffering gastroenteric diseases. This study included the systematic collection of Fs during the 2013–2017 period, from patients up to 14 years old. This manuscript has been approved by the appropriate ethical committees of the Ministerio de Salud Pública de la Provincia de Tucumán (Sección de Investigación en Salud-SIPROSA, Expediente N° 1134-410D-2019); Administración Nacional de Medicamentos, Alimentos y Tecnología Médica-Argentina (ANMAT) and the Registro Nacional de Investigaciones Sanitarias (ReNIS), which are related to the institutions (Public Hospitals) where it was performed. All participating members gave their informed consent as confidential data of each hospital.

Sample collection and pathogen identification methods

The stool samples were placed into sterile plastic containers, were maintained in Cary Blair medium and and transported to the laboratory. They were processed immediately after arrival, using the stool test. The samples were directly seeded in enrichment and selective/differential culture media plates as described in S1 Fig [1518]. The different clinical isolates (CI) were identified using the Hospitals’ standard biochemical tests as was described [1518].

Clinical isolates classification

All CIs obtained were classified by species and serotype levels with an antigenic analysis. The slide agglutination technique was carried out using specific sera obtained from ANLIS‐Malbrán.

The identification of S. flexneri and S. sonnei was prevalent. This was confirmed by multiplex PCR (mPCR) as was described [19]. The PCR products obtained from 10 CIs of each Shigella serotype were detected by electrophoresis in 1.2% agarose gels stained with ethidium bromide.

Antimicrobial susceptibility and plasmid analysis

Antimicrobial susceptibility tests were performed on Oxoid Müller–Hinton agar by the disk diffusion method. The antibiotics used were: ampicillin (Amp, 10 μg), chloramphenicol (Cm, 30 μg), kanamycin (Km, 30 μg), fosfomycin (200 μg), furazolidone (300 μg) and trimethoprim sulfamethoxazole (TMS, 1.25/23.75 μg). The antimicrobial susceptibility testing standards were performed following the CLSI recommendations. Resistance and sensitivity were interpreted according to the CLSI criteria [20].

The plasmid extraction was performed by the alkaline lysis method as was described [21]. The plasmids were analyzed by electrophoresis on agarose gels, stained with ethidium bromide and UV light exposition. Plasmid molecular size estimation was conducted by calibration curves using the Supercoiled Plasmidic DNA molecular marker (Promega).

Results

Gastrointestinal diseases incidence in the pediatric population of three NWA provinces

A total of 17 823 Fs from patients under 14 years old suffering acute diarrhea from three NWA Hospitals were collected and analyzed: 2,257 Fs from CePSI-Stgo; 1,324 from HINEP-Cat and 14 242 from HNJ-Tuc. The highest number of isolates (79.91% of the total) was registered in HNJ-Tuc, indicating that this population was the most affected (Fig 1A). Meanwhile the 12.66% and 7.43% were from CePSI-Stgo and HINEP-Cat, respectively (Fig 1A). In concordance with the size of the pediatric population estimated by Argentina’s INDEC [22, 23], we observed that the incidence of diarrheal diseases in Tucumán´s population was 33.01 of the total average. These results suggest that 33.01 children from 1,000 suffered at least one diarrheal disease episode during the analyzed period (Table 1). Conversely in Santiago del Estero and Catamarca the incidence was 8.5 and 12.6, respectively (Table 1). The pediatric population of the three provinces did not have major changes throughout the studied years (Table 1) [22, 23]. These data indicate that Tucumán displays 2 to 4-fold increased pediatric population than Santiago del Estero and Catamarca, respectively. Interestingly, when the incidence of diarrheal disease per year was analyzed in each province, a sharp decrease for 2015 was observed in Tucumán, while in the other provinces it remained relatively constant or weakly increased (Table 1).

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Fig 1. Isolation rates and incidence of infection disease agents in the NWA region´s Hospitals.

(A) Percentage of fecal samples (Fs) by Hospital, numbers of isolates are in parenthesis. (B) Cases numbers obtained per year in each Hospital.

https://doi.org/10.1371/journal.pone.0240404.g001

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Table 1. Incidence of gastroenteric disease in three provinces of NWA.

https://doi.org/10.1371/journal.pone.0240404.t001

The large number of cases recorded in HNJ-Tuc can be attributed to the high population density. Tucumán is the smallest surface province (22 524 km2) harboring 19 children/Km2, while Catamarca (102 602 km2) and Santiago del Estero (136 351 km2) have 1 and 2 children/Km2, respectively [10, 24]. Here, we observed that Tucumán has a 9.8- and 18-folds’ greater pediatric density compared to Santiago del Estero and Catamarca. The density levels were not correlated with the number of samples processed per year. The total number of Fs in HNJ-Tuc was, while in CePSI-Stgo remained high during 2014–2016; and in HINEP-Cat a marked increase was observed through the whole period (Fig 1B).

Enteric pathogens prevalence in the NWA region

Standard biochemical and microbiological diagnostics were performed to partially identify the bacterial agent present in the 17 823 Fs. Meanwhile, serological classification for species level was conducted by sera-specific tests. The results showed that in 14.55% (2,595 Fs) of the total studied cases at least one bacterial genus was isolated. The 93.64% of this 2,595 CI corresponded to the genus Shigella and Salmonella, placing them as the most common pathogens isolated (Table 2). Whereas in the remaining 6.36% (165 CI) others bacterial species such as Vibrio spp, Aeromona spp, E. coli O157:H7 and Campylobacter were identified (Table 2). We also observed that Salmonella had a lower occurrence than Shigella (6.96% vs 93.04%, Table 2) in the three hospitals. Interestingly, when the number of pathogens isolated was compared among the geographical areas, we found a higher percentage of Salmonella sp. (12.40%) in HINEP-Cat than in CEPSI-Stgo (2.5%) or HNJ-Tuc (6.92%) (Table 2).

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Table 2. Identification of bacterial agents causing gastroenteric disease in three provinces of NWA.

https://doi.org/10.1371/journal.pone.0240404.t002

We selected 10 CIs of each Shigella serotype from each hospital per year to confirm the serological classification using mPCR. In concordance with Farfán et al. (2010), the serum specific test results matched with the mPCR profiles (Fig 2A). These results demonstrated that Shigella genus is the prevalent pathogen in the study area, where S. flexneri was the most abundant specie (67 to 83% of CI) followed by S. sonnei (10 to 21%) (Fig 2B). In the three hospitals only 5 of the 14 S. flexneri serotypes were identified, being S. flexneri 2 (34.3%) the most frequent followed by S. flexneri AA479 (21%) and S. flexneri 1 (12%) (Fig 2C).

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Fig 2. Enteric bacteria incidence in the NWA´s province during the 2013–2017 period.

(A) Identification of S. flexneri and S. sonnei by molecular tools (mPCR). PCR products were analyzed by electrophoresis in 1.2% agarose, representative gel: 1- 1Kb Molecular marker: 2- S. sonnei (control); 3- S. flexneri non 2a (control); 4- S. flexneri 2a (control); 5- AC147;6- AC148; 7- AC152; 8- AC156; 9- AC159; 10- AC160; 11- AC161; 12- AC162; 13- AC163 and 14- AC168. (B) Number of Shigella clinical isolates identified per year in each Hospitals of the NWA region. (C) Incidence of the different S. flexneri´s serotypes isolated in the region. (D) Changes in the prevalence of Shigella serotypes in the NWA region, in recent years. (E) Incidence of the different Salmonella enteritidis serotypes identified during the study period.

https://doi.org/10.1371/journal.pone.0240404.g002

Using the database records from previous years (since 2010) in each hospital, we analyzed the S. flexneri AA479 and S. flexneri 2´s incidence. We found that S. flexneri AA479 was the prevalent pathogen in preceding years, but its prevalence drastically decreased over the years while the number of S. flexneri 2 isolations were increasing (Fig 2D).

As mentioned, Salmonella spp. was mainly isolated in Catamarca and Tucumán (Table 2). The serological analysis showed that only 10 different serovars of Salmonella enterica (S. enterica) were present in this region, being Typhimurium (S. Typhimurium, 67%) and Enteritidis (S. Enteritidis, 31%) serovars the prevalent ones (Fig 2E).

Geographical distribution of the studied pathogens

In Argentina the 30% of the bacterial infections reported affect the NWA [10]. We observed that 14.5% of the total Fs studied were caused by bacteria (Table 2). The incidence of the bacterial pathogen was analyzed considering its origin and the year of study. We observed that the number of CI in HNJ-Tuc remained relatively constant at high levels, while in the rest of the provinces these levels tended to decrease from 2015 (Fig 3A–3C). Moreover, we found that even when in HINEP-Cat a smaller number of Fs were processed, the number of CI was 2 folds higher than in CePSI-Stgo. In addition, during 2014 there was an increase in the number of CI in the three-sample collection areas, suggesting a possible epidemiological outbreak. We observed that the incidence of Shigella infections was the highest during 2014 (84–98%), since Shigella isolates outweighed Salmonella or other bacterial species isolations in all the analyzed places (Fig 3D–3F). Although only 2 of the 4 species of Shigella (S. flexneri and S. sonnei) were detected, the diversity of Shigella serovars was not homogeneous over the studied hospitals, and only 5 of 14 S. flexneri serovars were identified. Moreover, throughout the period analyzed in these places the increased persistence of S. flexneri 2 and the decrease of S. flexneri AA479 isolations remained constant. Remarkably, in HNJ-Tuc a high percentage S. sonnei (20–35%) was identified (Fig 3D).

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Fig 3. Ration of the bacterial CI´s number per year.

Ration of the bacterial CI´s number per year was related to the number of fecal samples obtained (A, B, C) and distribution of the pathogen genus isolated in each Fs (D, E, F) of the NWA´s Hospitals: HNS of Tucumán (A, D), CePSI of Santiago del Estero (B, E) and HINEP of Catamarca (C, F).

https://doi.org/10.1371/journal.pone.0240404.g003

Age range affected by the studied pathogens

In this study a range of age from newborns up to 14 years old was considered. We determined that the highest percentage of patients suffering such infection (around 50%) belonged to the age range between 1 to 4 years old (Fig 4A). However, it was also observed that 30% of the cases corresponds to a range of age of 5 to 9 years old, while children above 9 or younger than 1 were less susceptible to acquire the disease (10% each group) (Fig 4A).

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Fig 4. Distribution of the CIs according to the age of the patients and to the antibiotic resistance.

(A) Age distribution of the patients affected by gastrointestinal diseases during the 2013–2017 period, analyzing and taking into account the total number of patients from each NWA´s Hospitals. (B) Antibiotic Resistance Pattern (ARP). The antibiotic resistance of S. flexneri (full bar) and S. sonnei (striped bar) CIs obtained from HNJ-Tuc (black bar), CePSI-Stgo (dark gray bar) and HINEP-Cat (gray bar) was determined as described [16]. Twelve different patterns were obtained: ARP1 (Cm), ARP2 (Amp), ARP3 (TMS), ARP4 (Amp Cm), ARP5 (TMS Cm), ARP6 (Amp Km), ARP7 (Cm Km), ARP8 (TMS Amp), ARP9 (TMS Amp Km), ARP10 (Amp Cm Km), ARP11 (TMS Amp Cm) and ARP12 (TMS Amp Cm Km). S**: N° of CI sensitive to all antibiotics tested.

https://doi.org/10.1371/journal.pone.0240404.g004

Antimicrobial susceptibility pattern of the isolated pathogens

For a deeper analysis, we selected and stored 320 CIs, maintaining the ratio of Shigella and Salmonella’s serovars obtained per year and hospital (283 and 37 CIs, respectively). To characterize these CIs, antibiotic standard susceptibility tests were performed following the CLSI recommendations [20]. The results showed that 100% of Salmonella CI were sensitive to all the antibiotics analyzed, in contrast to 13% of 283 Shigella CIs were sensitive (Fig 4B). The remaining 87% of Shigella CIs were clustered into 12 different antibiotic resistance patterns (ARP) of 36 putative combinations (Fig 4B).

In HNJ-Tuc 12 different ARPs were presented, containing at least one S. flexneri CI (Fig 4B). The MDR-ARP-4 was the most abundant group followed by ARP-11 and ARP-12. In CePSI-Stgo the ARP-11 included the largest number of CI, while in HINEP-Cat the ARP-4 and ARP-1 patterns were prevalent. Almost all the S. sonnei CIs displayed non antimicrobial resistance, except in HNJ-Tuc where the highest number of S. sonnei was Amp resistant. These results showed that the prevalent pathogenic strains presented themselves as MDR bacteria, containing between 2 and 3 genetic determinants of resistance. Interestingly, the Amp resistance was the most widely distributed among these pathogens regardless of place and year of isolation.

We also analyzed the plasmid content of the CIs belonging to the most persistent ARP groups. Using a molecular marker, we were able to infer the number and size of the putative plasmids showing a great variety of them (Table 3). We observed that the great diversity in plasmid content is present not only inter S. flexneri and S. sonnei but also intra species (Table 3). As shown in Table 3, the wide diversity of plasmids was fully distributed over each ARP groups. Two to three plasmid profiles were found among the multidrug-resistant strains of S. flexneri, which were independent of the place and the year of isolation. Among the S. sonnei isolates selected according to their antimicrobial susceptibility group, two plasmid profiles sharing a plasmid of approximately 6.0 kb were observed.

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Table 3. Plasmid content of Shigella clinical isolates belonging to the most frequent antimicrobial resistance profiles.

https://doi.org/10.1371/journal.pone.0240404.t003

Discussion

Gastroenteric infections are among the main causes of morbidity and mortality of pediatric population [9]. The number of reported cases puts Argentina at the same level as Cuba and 307.5% higher than Chile [10]. We carried out an epidemiology study to determine the gastroenteritis incidence in NWA pediatric population, since there were no reports showing the epidemiological status of this region. When the average of these province’s population size [11, 22] was considered, we observed that 2.2% of children suffered at least one diarrhea episode during this period, where 11.3% of the total were produced by some bacterial agent. In this period there was an increase in the number of patients with gastroenteritis, mainly in HINEP-Cat where this increase was more distinct. Despite the increased number of Fs obtained, the CI number was slightly diminished, except in CePSI-Stgo where a significant reduction was observed. Conversely the pediatric population of Tucumán was the most affected per year, probably due to the high population density concentrated in the urban area of this province. This suggestion was based on the data reported by INDEC 2010, where Tucumán´s population exceeded 1.7 and 4 times the Santiago del Estero and Catamarca populations [11]. In Tucumán the rate of Fs/CI was maintained along the years of study, suggesting that the bacterial infections could not be controlled, at least in this region. We observed that the flow of admitted children in HNJ-Tuc was also higher than in CePSI-Stgo and HINEP-Cat (6.4 and 10-fold respectively), suggesting that this increased flow occurs by person-to-person transmission due to the high population density. Meanwhile, in Santiago del Estero and Catamarca other factors as the economy, hygiene and health conditions may be the major influencers. However, when the pediatric population size and the flow of patients per province were considered it was observed that Catamarca is the province with the highest percentage of positive bacterial cases.

During 2014, the total number of Fs analyzed was greater than the previous year, suggesting that an infectious outbreak could have occurred. These data is correlated with previous reports, in which during 2014 and 2016 the rate of gastrointestinal diseases was around 10 and 40 times higher than the vectorial and Zoonotic Immuno-preventable diseases, respectively [24]. Our results suggest that this outbreak was caused by bacterial agents, since we was also observed a ≅1.4 to 3-fold increase in the number of CI.

In accordance with previous reports we observed that about 10% of the total cases of bacterial infection corresponded to newborns (0 and 1 year old), while the most affected were the children between 1 to 4 years old (~55%) [2527].

We demonstrated that in the NWA, Shigella isolates were more frequent (87.12%) than reported in other Argentina´s regions [2832]. The presence of Shigella is used as an indicator of hygiene level: S. flexneri is isolated in poorer regions while S. sonnei is identified in industrialized areas. Our serotyping results indicated that the number of S. flexneri isolations was higher than S. sonnei. These results confirm the poverty degree of the NWA region as was reported [33, 34]. The percentage of poor people residing in the NWA is five times bigger than in Buenos Aires city (Argentina`s capital) and almost triple than Southern Patagonia [33, 35]. In addition, we demonstrated that S. flexneri 2 isolations increased over the number of S. flexneri AA479, positioning itself as the prevalent pathogen of the NWA region. In concordance, Merino et al. reported that S. flexneri 2 was the prevalent pathogen in the Northeast region of Argentina (NEA) [30].

In this study, S. flexneri strains isolated showed a multidrug-resistant pattern. However, a high frequency of ampicillin or chloramphenicol resistant isolates was also observed. We can suggest that over time the CIs belonging to ARP-4 (AmpRCmR) could sequentially acquire 1 or 2 determinant antibiotic resistance genes (TMSR for ARP-11 and TMSR KmR for ARP-12) to become MDR strains, due to the wide and indiscriminate use of antimicrobial drugs [36, 37]. The identification of Shigella MDR isolates was also reported in NEA, but with a different pattern [30]. Despite the fact that we could not find a direct relation between the plasmid patterns and the ARPs, the great diversity observed suggests the horizontal gene transfer as a possible mechanism to spread these resistances among the pathogens affecting the NWA population.

Supporting information

S1 Fig. Steps followed for pathogens isolation from fecal sample.

MacConkey: selective/differential medium. XLD agar: selective medium. Salmonella/Shigella agar (SS agar): selective/differential medium. Selenito Broth/Tetrationato: enrichment media. Scheme adapted from the Microbiological Procedure Handbook of Koneman, E.W. and Allen, S. (2008) and Murray, P.R. (2013), routinely used in the Bacteriology´s labs of the Hospitals involved in this study [18].

https://doi.org/10.1371/journal.pone.0240404.s001

(PDF)

Acknowledgments

We thank to the Biochemical technicians and to Directors from the different hospitals that collaborated with the samples collection, and to Dra. Marcela Bonano and Bqca. Cecilia del Valle Vallejos for the technical assistance. M.F.Torrez Lamberti is a Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET) fellow. P. Valdez, A. Bianchi and E. Barrionuevo Medina are the HINEP, CePSI and HNJ `s bacteriology laboratory chiefs; respectively. F.E. López, M.M. Pescaretti and M.A. Delgado are researchers from Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET).

References

  1. 1. World Health Organization (WHO) (1996) Scientific working group, resistance to antimicrobial agents. Bull World Health Organ 71: 335–336.
  2. 2. Prado V, O'Ryan ML (1994) Acute gastroenteritis in Latin America. Infect Dis Clin North Am 8: 77–106. pmid:8021450
  3. 3. Suarez MC, Mantilla JR (2000) Presencia de Salmonella serovariedad Enteritidis en productos de origen avícola y su repercusión en salud pública. IATREIA/VOL 13/No4/.
  4. 4. Delgado L, Carrero A, Hernández J, Blanco B, Schael I (1999) Origen bacteriano de la enfermedad diarreica aguda en Mérida, Venezuela. Rev Cubana Med Trop 51: 9–14.
  5. 5. Ministerio de Salud Gobierno Argentino (2008) Convivencia humano-animal Zoonosis Instituto de Zoonosis Luis Pasteur, Área de Educación para la Salud Residencia de Educación para la Salud Material producido por el Equipo del Área de Educación para la Salud del Instituto Luis Pasteur y la Residencia Interdisciplinaria de Educación para la Salud. pp. 11–16.
  6. 6. Scherer CA, Miller SI (2001) Molecular pathogenesis of Salmonella. In In Principles of Bacterial Pathogenesis.; Groisman EA, (ed.), editor. New York: Academic Press. 266–333. p.
  7. 7. D'Souza RM, Becker NG, Hall G, Moodie KB (2004) Does ambient temperature affect foodborne disease? Epidemiology 15: 86–92. pmid:14712151
  8. 8. Black RE, Cousens S, Johnson HL, Lawn JE, Rudan I, et al. (2010) Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet 375: 1969–1987. pmid:20466419
  9. 9. World Health Organization (WHO) (1996) The world health report 1996. World Health Organization.
  10. 10. Rubinstein A, Aruachan D, Burgos M, Angeleri PI (2018) Boletín Integrado de Vigilancia. Direccion Nacional de Epidemiologia y Analsis de la Situacion de Salud Ministerio de Salud de la Nación Argentina: 1–90.
  11. 11. Edwin AM, INDEC (2012) Censo Nacional de Población, Hogares y Viviendas 2010. Censo del Bicentenario. Instituto Nacional de Estadística y Censos -Argentina (INDEC) Serie B N° 2: 378.
  12. 12. Ray B, Bhunia A (2007) Important facts in foodborne diseases Fundamental Food Microbiology, Fourth Edition (CRC Press): 253–267.
  13. 13. World Health Organization (WHO) (2004) Risk assessment of Listeria monocytogenes in ready-to-eat foods, World Health Organization, Food and Agriculture Organization of the United Nations.
  14. 14. Degiuseppe JI (2017) Trends in hospital discharges for intestinal infectious disease in infants in Argentina, 2005–2013. Arch Argent Pediatr 115: 6.
  15. 15. Vandepitte J, Engbaek Kraesten, Piot Peter, et al. (2003) Basic laboratory procedures in clinical bacteriology. World Health Organization.
  16. 16. Koneman EW, Stephen A (2008) Diagnostico Microbiologico/ Microbiological diagnosis. Ed. Médica Panamericana. 1691 p.
  17. 17. Murray PR (2013) Microbiología médica.: Elsevier. 872 p.
  18. 18. Vallejos C, Lomenzo G (2017) Manual Microbiología- Bacteriología: II) Procesamiento de muestras Ministerio de Salud Publica Argentina-Hospital Eva Peron-Sistema Provincial de Salud-Tucuman: 25.
  19. 19. Farfan MJ, Garay TA, Prado CA, Filliol I, Ulloa MT, et al. (2010) A new multiplex PCR for differential identification of Shigella flexneri and Shigella sonnei and detection of Shigella virulence determinants. Epidemiol Infect 138: 525–533. pmid:19765332
  20. 20. Barry AL, Craig W, Nadler H, Reller LB, Sanders CC, et al. (2011) Methods for Determining Bactericidal Activity of Antimicrobial Agents. Clinical And Laboratory Standards Institute.
  21. 21. Birnboim HC, Doly J (1979) A rapid alkaline extraction procedure for screening recombinant plasmid DNA. Nucleic Acids Res 7: 1513–1523. pmid:388356
  22. 22. Fernández MM, Guevel CG, Peyton MS, Grünwaldt ME (2014) Estadisticas vitales informacion basica—Año 2013. Ministerio de Salud Publica de Argentina: Sistema Estadistico de Salud INDEC Serie 5 -: 1–150.
  23. 23. Nielen MMJ, Spronk I, Davids R, Korevaar JC, Poos R, et al. (2019) Estimating Morbidity Rates Based on Routine Electronic Health Records in Primary Care: Observational Study. JMIR Med Inform 7: e11929. pmid:31350839
  24. 24. Marconi EH, Fernández MM, Guevel CG, Peyton MS, Grünwaldt ME (2014) Estadisticas vitales-informacion basica—AÑO 2013. Ministerio de Salud de la Nacion Argentina Secretaria de Politicas, Regulacion e Institutos Direccion de estadisticas e informacion de salud 5 150.
  25. 25. Kuchenmuller T, Abela-Ridder B, Corrigan T, Tritscher A (2013) World Health Organization initiative to estimate the global burden of foodborne diseases. Rev Sci Tech 32: 459–467. pmid:24547649
  26. 26. Martorell R, Yarbrough C, Yarbrough S, Klein RE (1980) The impact of ordinary illnesses on the dietary intakes of malnourished children. Am J Clin Nutr 33: 345–350. pmid:7355806
  27. 27. Borruel M, Mas P, Borruel G (2010) Estudio de carga de enfermedad: Argentina. Proyecto Funciones Esenciales y Programas Priorizados en Salud Pública (FESP) Ministerio de Salud de la Nación: 320.
  28. 28. Casabonne C, Gonzalez A, Aquili V, Balague C (2016) Prevalence and Virulence Genes of Shigella spp. Isolated from Patients with Diarrhea in Rosario, Argentina. Jpn J Infect Dis 69: 477–481. pmid:26902216
  29. 29. Chapur VF, Alfaro EL, Bronberg R, Dipierri JE (2017) Relationship between infant mortality and altitude in the Northwest region of Argentina. Arch Argent Pediatr 115: 462–469. pmid:28895693
  30. 30. Merino LA, Hreñuk GE, Ronconi MC, Alonso JM (2004) Resistencia a antibióticos y epidemiología molecular de Shigella spp. en el nordeste argentino. Rev Panam Salud Publica 15: 5.
  31. 31. Rolfo F, Marin GH, Silberman M, Pattin J, Giugnio S, et al. (2012) Epidemiological study of shigellosis in an urban area of Argentina. J Infect Dev Ctries 6: 324–328. pmid:22505441
  32. 32. Vargas MA, Bartoli C, Tacchini MM, Nóbile C, Figueroa M (2017) Agentes etiológicos causantes de diarrea aguda aislados en pacientes que concurren a un hospital público polivalente de la ciudad de Córdoba durante el período 2013–2015 Colegio de Bioquímicos de la Provincia de Córdoba Publicaciones Científicas: 16.
  33. 33. Instituto Nacional de Estadística y Censos de la República Argentina (INDEC) (2017) Incidencia de la pobreza y la indigencia en 31 aglomerados urbanos.
  34. 34. United Nations International Children's Emergency Fund (UNICEF) (2017) Salud Materno Infanto Juvenil en Cifras.
  35. 35. Instituto Nacional de Estadística y Censos de la República Argentina (INDEC) (2016) Incidencia de la pobreza y de la indigencia en 31 aglomerados urbanos.
  36. 36. Zamanlou S, Ahangarzadeh Rezaee M, Aghazadeh M, Ghotaslou R, Babaie F, et al. (2018) Characterization of integrons, extended-spectrum beta-lactamases, AmpC cephalosporinase, quinolone resistance, and molecular typing of Shigella spp. from Iran. Infect Dis (Lond): 1–9.
  37. 37. Zamanlou S, Rezaee MA, Aghazadeh M, Ghotaslou R, Nave HH, et al. (2018) Genotypic Diversity of Multidrug Resistant Shigella species from Iran. Infect Chemother 50: 29–37. pmid:29637750