Current Environmental Health Reports

, Volume 5, Issue 2, pp 293–304 | Cite as

Quantitative Microbial Risk Assessment and Infectious Disease Transmission Modeling of Waterborne Enteric Pathogens

  • Andrew F. Brouwer
  • Nina B. Masters
  • Joseph N. S. Eisenberg
Water and Health (T Wade, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Water and Health


Purpose of Review

Waterborne enteric pathogens remain a global health threat. Increasingly, quantitative microbial risk assessment (QMRA) and infectious disease transmission modeling (IDTM) are used to assess waterborne pathogen risks and evaluate mitigation. These modeling efforts, however, have largely been conducted independently for different purposes and in different settings. In this review, we examine the settings where each modeling strategy is employed.

Recent Findings

QMRA research has focused on food contamination and recreational water in high-income countries (HICs) and drinking water and wastewater in low- and middle-income countries (LMICs). IDTM research has focused on large outbreaks (predominately LMICs) and vaccine-preventable diseases (LMICs and HICs).


Human ecology determines the niches that pathogens exploit, leading researchers to focus on different risk assessment research strategies in different settings. To enhance risk modeling, QMRA and IDTM approaches should be integrated to include dynamics of pathogens in the environment and pathogen transmission through populations.


Quantitative microbial risk assessment Infectious disease transmission modeling Waterborne pathogen Enteric disease Human ecology 


Compliance with Ethical Standards

Conflict of Interest

Nina B. Masters, Andrew F. Brouwer and Joseph N. S. Eisenberg were supported by the NIGMS MIDAS program (grant #: U01GM110712). The authors report no other conflict of interests.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Supplementary material

40572_2018_196_MOESM1_ESM.pdf (101 kb)
ESM 1 (PDF 100 kb)


Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. 1.
    GBD 2015 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388(10053):1459–1544.Google Scholar
  2. 2.
    Julian TR. Environmental transmission of diarrheal pathogens in low and middle income countries. Environ Sci: Process Impacts. 2016;18(8):944–55.Google Scholar
  3. 3.
    Curriero FC, Patz JA, Rose JB, Lele S. The Association Between Extreme Precipitation and Waterborne Disease Outbreaks in the United States, 1948–1994. Am J Public Health. 2001;91(8):1194–9.PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Wade TJ, Sandhu SK, Levy D, Lee S, LeChevallier MW, Katz L, et al. Did a Severe Flood in the Midwest Cause an Increase in the Incidence of Gastrointestinal Symptoms? Am J Epidemiol. 2004;159(4):398–405.PubMedCrossRefGoogle Scholar
  5. 5.
    Levy K, Woster AP, Goldstein RS, Carlton EJ. Untangling the Impacts of Climate Change on Waterborne Diseases: A Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought. Environ Sci Technol. 2016;50(10):4905–22.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Lo Iacono G, Armstrong B, Fleming LE, Elson R, Kovats S, Vardoulakis S, et al. Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review. PLoS Negl Trop Dis. 2017;11(6):e0005659.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Eisenberg JNS, Trostle J, Sorensen RJD, Shields KF. Toward a Systems Approach to Enteric Pathogen Transmission: From Individual Independence to Community Interdependence. Annu Rev Public Health. 2012;33(1):239–57.PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Levine MM, Levine OS. Changes in human ecology and behavior in relation to the emergence of diarrheal diseases, including cholera. Proc Natl Acad Sci. 1994;91(7):2390–4.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Haas CN, Rose JB, Gerba CP. Quantitative Microbial Risk Assessment. Hoboken, NJ: John Wiley & Sons, Inc.; 2014.Google Scholar
  10. 10.
    Haas CN. Estimation of risk due to low doses of microorganisms: a comparison of alternative methodologies. Am J Epidemiol. 1983;118(4):573–82.PubMedCrossRefGoogle Scholar
  11. 11.
    Rose JB, Haas CN, Regli S. Risk assessment and control of water borne giardiasis. Am J Public Health. 1991;81(6):709–13.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Haas CN, Rose JB, Gerba C, Regli S. Risk assessment of virus in drinking water. Risk Anal : Off Publ Soc Risk Anal. 1993;13(5):545–52.CrossRefGoogle Scholar
  13. 13.
    Teunis PFM, van der Heijden OG, van der Giessen JWB, Havelaar AH. The dose-response relation in human volunteers for gastro-intestinal pathogens. Bilthoven, The Netherlands: National Institute of Public Health and the. Environment. 1996;Google Scholar
  14. 14.
    Teunis PFM, Nagelkerke NJD, Haas CN. Dose response models for infectious gastroenteritis. Risk Anal. 1999;19(6):1251–60.PubMedGoogle Scholar
  15. 15.
    Kermack WO, McKendrick AG. A contribution to the mathematical theory of epidemics. Proc Royal Soc A: Math Phys Eng Sci. 1927;115(772):700–21.CrossRefGoogle Scholar
  16. 16.
    Eisenberg JNS, Brookhart MA, Rice G, Brown M, Colford JM. Disease transmission models for public health decision making: Analysis of epidemic and endemic conditions caused by waterborne pathogens. Environ Health Perspect. 2002;110(8):783–90.PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Eisenberg JNS, Lei X, Hubbard AH, Brookhart MA, Colford JM. The role of disease transmission and conferred immunity in outbreaks: Analysis of the 1993 Cryptosporidium outbreak in Milwaukee, Wisconsin. Am J Epidemiol. 2005;161(1):62–72.PubMedCrossRefGoogle Scholar
  18. 18.
    Codeço CT. Endemic and epidemic dynamics of cholera: the role of the aquatic reservoir. BMC Infect Dis. 2001;1(1)Google Scholar
  19. 19.
    Chick SE, Koopman JS, Soorapanth S, Brown ME. Infection transmission system models for microbial risk assessment. Sci Total Environ. 2001;274(1-3):197–207.PubMedCrossRefGoogle Scholar
  20. 20.
    Li S, Spicknall IH, Koopman JS, Eisenberg JNS. Dynamics and control of infections transmitted from person to person through the environment. Am J Epidemiol. 2009;170(2):257–65.PubMedCrossRefGoogle Scholar
  21. 21.
    Tien JH, Earn DJD. Multiple transmission pathways and disease dynamics in a waterborne pathogen model. Bull Math Biol. 2010;72(6):1506–33.PubMedCrossRefGoogle Scholar
  22. 22.
    Kobayashi N, Oshiki M, Ito T, Segawa T, Hatamoto M, Kato T, et al. Removal of human pathogenic viruses in a down-flow hanging sponge (DHS) reactor treating municipal wastewater and health risks associated with utilization of the effluent for agricultural irrigation. Water Res. 2017;110:389–98.PubMedCrossRefGoogle Scholar
  23. 23.
    Pecson BM, Triolo SC, Olivieri S, Chen EC, Pisarenko AN, Yang CC, et al. Reliability of pathogen control in direct potable reuse: Performance evaluation and QMRA of a full-scale 1 MGD advanced treatment train. Water Res. 2017;122:258–68.PubMedCrossRefGoogle Scholar
  24. 24.
    Chaudhry RM, Hamilton KA, Haas CN, Nelson KL. Drivers of microbial risk for direct potable reuse and de facto reuse treatment schemes: The impacts of source water quality and blending. Int J Environ Res Public Health. 2017;14(6):1–20.CrossRefGoogle Scholar
  25. 25.
    Amoueyan E, Ahmad S, Eisenberg JNS, Pecson B, Gerrity D. Quantifying pathogen risks associated with potable reuse: A risk assessment case study for Cryptosporidium. Water Res. 2017;119:252–66.PubMedCrossRefGoogle Scholar
  26. 26.
    Chhipi-Shrestha G, Hewage K, Sadiq R. Microbial quality of reclaimed water for urban reuses: Probabilistic risk-based investigation and recommendations. Sci Total Environ. 2017;576:738–51.PubMedCrossRefGoogle Scholar
  27. 27.
    Krkosek W, Reed V, Gagnon GA. Assessing protozoan risks for surface drinking water supplies in Nova Scotia, Canada. J Water Health. 2016;14(1):155–66.PubMedCrossRefGoogle Scholar
  28. 28.
    • Sokolova E, Petterson SR, Dienus O, Nystrom F, Lindgren PE, Pettersson TJR. Microbial risk assessment of drinking water based on hydrodynamic modelling of pathogen concentrations in source water. Science of the Total Environment. 2015; 526:177–186. This analysis incorporated hydrological dynamics into a QMRA of norovirus in drinking water. Google Scholar
  29. 29.
    Amha YM, Kumaraswamy R, Ahmad F. A probabilistic QMRA of Salmonella in direct agricultural reuse of treated municipal wastewater. Water Sci Technol. 2015;71(8):1203–11.PubMedCrossRefGoogle Scholar
  30. 30.
    Mok HF, Barker SF, Hamilton AJ. A probabilistic quantitative microbial risk assessment model of norovirus disease burden from wastewater irrigation of vegetables in Shepparton, Australia. Water Res. 2014;54:347–62.PubMedCrossRefGoogle Scholar
  31. 31.
    Agulló-Barceló M, Casas-Mangas R, Lucena F. Direct and indirect QMRA of infectious cryptosporidium oocysts in reclaimed water. J Water Health. 2012;10(4):539–48.Google Scholar
  32. 32.
    Pintar KDM, Fazil A, Pollari F, Waltner-Toews D, Charron DF, Mcewen SA, et al. Considering the risk of infection by cryptosporidium via consumption of municipally treated drinking water from a surface water source in a southwestern Ontario community. Risk Anal. 2012;32(7):1122–38.PubMedCrossRefGoogle Scholar
  33. 33.
    Farakos SMS, Pouillot R, Johnson R, Spungen J, Son I, Anderson N, et al. A Quantitative assessment of the risk of human salmonellosis arising from the consumption of almonds in the United States: The impact of preventive treatment levels. J Food Prot. 2017;80(5):863–78.CrossRefGoogle Scholar
  34. 34.
    Farakos SMS, Pouillot R, Johnson R, Spungen J, Son I, Anderson N, et al. A Quantitative assessment of the risk of human salmonellosis arising from the consumption of pecans in the United States. J Food Prot. 2017;80(9):1574–91.PubMedCrossRefGoogle Scholar
  35. 35.
    Møller COA, Nauta MJ, Schaffner DW, Dalgaard P, Christensen BB, Hansen TB. Risk assessment of Salmonella in Danish meatballs produced in the catering sector. Int J Food Microbiol. 2015;196:109–25.PubMedCrossRefGoogle Scholar
  36. 36.
    Gayán E, Torres JA,´ Álvarez I, Condón S. Selection of process conditions by risk assessment for apple juice pasteurization by UV-heat treatments at moderate temperatures. J Food Prot 2014; 77(2):207–215.PubMedCrossRefGoogle Scholar
  37. 37.
    Praveen C, Dancho BA, Kingsley DH, Calci KR, Meade GK, Mena KD, et al. Susceptibility of murine norovirus and hepatitis a virus to electron beam irradiation in oysters and quantifying the reduction in potential infection risks. Appl Environ Microbiol. 2013;79(12):3796–801.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Espinosa AC, Jesudhasan P, Arredondo R, Cepeda M, Mazari-Hiriart M, Mena KD, et al. Quantifying the reduction in potential health risks by determining the sensitivity of poliovirus type 1 chat strain and rotavirus SA-11 to electron beam irradiation of iceberg lettuce and spinach. Appl Environ Microbiol. 2012;78(4):988–93.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Tamimi AH, Maxwell S, Edmonds SL, Gerba CP. Impact of the use of an alcohol-based hand sanitizer in the home on reduction in probability of infection by respiratory and enteric viruses. Epidemiol Infect. 2015;143(15):3335–41.PubMedCrossRefGoogle Scholar
  40. 40.
    Ryan MO, Haas CN, Gurian PL, Gerba CP, Panzl BM, Rose JB. Application of quantitative microbial risk assessment for selection of microbial reduction targets for hard surface disinfectants. Am J Infect Control. 2014;42(11)Google Scholar
  41. 41.
    Schaffner DW, Bowman JP, English DJ, Fischler GE, Fuls JL, Krowka JF, et al. Quantitative Microbial Risk Assessment of Antibacterial Hand Hygiene Products on Risk of Shigellosis. J Food Prot. 2014;77(4):574–82.PubMedCrossRefGoogle Scholar
  42. 42.
    Benami M, Busgang A, Gillor O, Gross A. Quantification and risks associated with bacterial aerosols near domestic greywatertreatment systems. Sci Total Environ. 2016;562:344–52.PubMedCrossRefGoogle Scholar
  43. 43.
    Matthews L, Reeve R, Gally DL, Low JC, Woolhouse MEJ, McAteer SP, et al. Predicting the public health benefit of vaccinating cattle against Escherichia coli O157. Proc Natl Acad Sci. 2013;110(40):16265–70.PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Dalahmeh SS, Lalander C, Pell M, Vinnerås B, Jönsson H. Quality of greywater treated in biochar filter and risk assessment of gas-¨ troenteritis due to household exposure during maintenance and irrigation. J Appl Microbiol. 2016;121(5):1427–43.PubMedCrossRefGoogle Scholar
  45. 45.
    Petterson SR. Application of a QMRA framework to inform selection of drinking water interventions in the developing context. Risk Anal. 2016;36(2):203–14.PubMedCrossRefGoogle Scholar
  46. 46.
    Reygadas F, Gruber JS, Ray I, Nelson KL. Field efficacy evaluation and post-treatment contamination risk assessment of an ultraviolet disinfection and safe storage system. Water Res. 2015;85:74–84.PubMedCrossRefGoogle Scholar
  47. 47.
    Coulliette AD, Enger KS, Weir MH, Rose JB. Risk reduction assessment of waterborne Salmonella and Vibrio by a chlorine contact disinfectant point-of-use device. Int J Hyg Environ Health. 2013;216(3):355–61.PubMedCrossRefGoogle Scholar
  48. 48.
    Rodriguez-Alvarez MS, Weir MH, Pope JM, Seghezzo L, Rajal VB, Salusso MM, et al. Development of a relative risk model for drinking water regulation and design recommendations for a peri urban region of Argentina. Int J Hyg Environ Health. 2015;218(7):627–38.PubMedCrossRefGoogle Scholar
  49. 49.
    Zhang Y, Chen Z, An W, Xiao S, Yuan H, Zhang D, et al. Risk assessment of Giardia from a full scale MBR sewage treatment plant caused by membrane integrity failure. J Environ Sci (China). 2015;30:252–8.CrossRefGoogle Scholar
  50. 50.
    Teklehaimanot GZ, Genthe B, Kamika I, Momba MNB. Prevalence of enteropathogenic bacteria in treated effluents and receiving water bodies and their potential health risks. Sci Total Environ. 2015;518-519:441–9.PubMedCrossRefGoogle Scholar
  51. 51.
    Symonds EM, Verbyla ME, Lukasik JO, Kafle RC, Breitbart M, Mihelcic JR. A case study of enteric virus removal and insights into the associated risk of water reuse for two wastewater treatment pond systems in Bolivia. Water Res. 2014;65:257–70.PubMedCrossRefGoogle Scholar
  52. 52.
    Cutolo SA, Piveli RP, Santos JG, Montes CR, Sundefeld G, Campos F, et al. Parasitological risk assessment from wastewater reuse for disposal in soil in developing countries. Water Sci Technol. 2012;65(8):1357–67.PubMedCrossRefGoogle Scholar
  53. 53.
    Kinyua MN, Wald I, Camacho-Céspedes F, Izurieta R, Haas CN, Ergas SJ. Does the use of tubular digesters to treat livestock waste lower the risk of infection from Cryptosporidium parvum and Giardia lamblia? J Water Health 2016; 14(5):738– 753.Google Scholar
  54. 54.
    Chaidez C, Soto-Beltran M, Gerba CP, Tamimi AH. Reduction of risk of Salmonella infection from kitchen cleaning clothes by use of sodium hypochlorite disinfectant cleaner. Lett Appl Microbiol. 2014;59(5):487–92.PubMedCrossRefGoogle Scholar
  55. 55.
    Burch TR, Spencer SK, Stokdyk JP, Kieke BA, Larson RA, Firnstahl AD, et al. Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model. Environ Health Perspect. 2017;125(8):1–11.CrossRefGoogle Scholar
  56. 56.
    Courault D, Albert I, Perelle S, Fraisse A, Renault P, Salemkour A, et al. Assessment and risk modeling of airborne enteric viruses emitted from wastewater reused for irrigation. Sci Total Environ. 2017;592:512–26.PubMedCrossRefGoogle Scholar
  57. 57.
    Clarke R, Peyton D, Healy MG, Fenton O, Cummins E. A quantitative microbial risk assessment model for total coliforms and E. coli in surface runoff following application of biosolids to grassland. Environ Pollut. 2017;224:739–50.PubMedCrossRefGoogle Scholar
  58. 58.
    Makkaew P, Miller M, Fallowfield HJ, Cromar NJ. Microbial risk in wastewater irrigated lettuce: Comparing Escherichia coli contamination from an experimental site with a laboratory approach. Water Sci Technol. 2016;74(3):749–55.PubMedCrossRefGoogle Scholar
  59. 59.
    Beaudequin D, Harden F, Roiko A, Mengersen K. Utility of Bayesian networks in QMRA-based evaluation of risk reduction options for recycled water. Sci Total Environ. 2016;541:1393–409.PubMedCrossRefGoogle Scholar
  60. 60.
    Dungan RS. Estimation of infectious risks in residential populations exposed to airborne pathogens during center pivot irrigation of dairy wastewaters. Environ Sci Technol. 2014;48(9):5033–42.PubMedCrossRefGoogle Scholar
  61. 61.
    Barker SF, Amoah P, Drechsel PA. probabilistic model of gastroenteritis risks associated with consumption of street food salads in Kumasi, Ghana: Evaluation of methods to estimate pathogen dose from water, produce or food quality. Sci Total Environ. 2014;487(1):130–42.PubMedCrossRefGoogle Scholar
  62. 62.
    Schmidt PJ, Emelko MB, Thompson ME. Analytical recovery of protozoan enumeration methods: Have drinking water QMRA models corrected or created bias? Water Res. 2013;47(7):2399–408.PubMedCrossRefGoogle Scholar
  63. 63.
    Barker SF, O’Toole J, Sinclair MI, Leder K, Malawaraarachchi M, Hamilton AJ. A probabilistic model of norovirus disease burden associated with greywater irrigation of home-produced lettuce in Melbourne, Australia. Water Res. 2013;47(3):1421–32.CrossRefGoogle Scholar
  64. 64.
    Aiello R, Cirelli GL, Consoli S, Licciardello F, Toscano A. Risk assessment of treated municipal wastewater reuse in Sicily. Water Sci Technol. 2013;67(1):89–98.PubMedCrossRefGoogle Scholar
  65. 65.
    Shrestha S, Haramoto E, Shindo J. Assessing the infection risk of enteropathogens from consumption of raw vegetables washed with contaminated water in Kathmandu Valley, Nepal. J Appl Microbiol. 2017;Google Scholar
  66. 66.
    Henao-Herreño LX, López-Tamayo AM, Ramos-Bonilla JP, Haas CN, Husserl J. Risk of illness with Salmonella due to consumption of raw unwashed vegetables irrigated with water from the Bogota River. Risk Anal. 2017;37(4):733–43.PubMedCrossRefGoogle Scholar
  67. 67.
    Owusu-Ansah EGJ, Sampson A, Amponsah SK, Abaidoo RC, Dalsgaard A, Hald T. Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose. Sci Total Environ. 2017;601-602:1712–9.PubMedCrossRefGoogle Scholar
  68. 68.
    Le-Thi T, Pham-Duc P, Zurbrügg C, Luu-Quoc T, Nguyen-Mai H, Vu-Van T, et al. Diarrhea risks by exposure to livestock waste in Vietnam using quantitative microbial risk assessment. Int J Public Health. 2017;62:83–91.PubMedCrossRefGoogle Scholar
  69. 69.
    Verbyla ME, Symonds EM, Kafle RC, Cairns MR, Iriarte M, Mercado Guzmán A, et al. Managing Microbial Risks from Indirect Wastewater Reuse for Irrigation in Urbanizing Watersheds. Environ Sci Technol. 2016;50(13):6803–13.PubMedCrossRefGoogle Scholar
  70. 70.
    Krzyzanowski F, de Souza Lauretto M, Nardocci AC, Sato MIZ, Razzolini MTP. Assessing the probability of infection by Salmonella due to sewage sludge use in agriculture under several exposure scenarios for crops and soil ingestion. Sci Total Environ. 2016;568:66–74.PubMedCrossRefGoogle Scholar
  71. 71.
    Antwi-Agyei P, Cairncross S, Peasey A, Price V, Bruce J, Baker K, et al. A farm to fork risk assessment for the use of wastewater in agriculture in Accra, Ghana. PLoS One. 2015;10(11):1–19.CrossRefGoogle Scholar
  72. 72.
    Seidu R, Abubakari A, Dennis IA, Heistad A, Stenstrom TA, Larbi JA, et al. A probabilistic assessment of the contribution of wastewater-irrigated lettuce to Escherichia coli O157:H7 infection risk and disease burden in Kumasi, Ghana. J Water Health. 2015;13(1):217–29.PubMedCrossRefGoogle Scholar
  73. 73.
    Pavione DMS, Bastos RKX, Bevilacqua PD. Quantitative microbial risk assessment applied to irrigation of salad crops with waste stabilization pond effluents. Water Sci Technol. 2013;67(6):1208–15.PubMedCrossRefGoogle Scholar
  74. 74.
    Kobayashi Y, Peters GM, Ashbolt NJ, Heimersson S, Svanström M, Khan SJ. Global and local health burden trade-off through the hybridisation of quantitative microbial risk assessment and life cycle assessment to aid water management. Water Res. 2015;79:26–38.PubMedCrossRefGoogle Scholar
  75. 75.
    Yapo RI, Koné B, Bonfoh B, Cissé G, Zinsstag J, Nguyen-Viet H. Quantitative microbial risk assessment related to urban wastewater and lagoon water reuse in Abidjan, Cote d’Ivoire. J Water Health. 2014;12(2):301–9.PubMedCrossRefGoogle Scholar
  76. 76.
    Hamilton KA, Ahmed W, Palmer A, Sidhu JPS, Hodgers L, Toze S, et al. Public health implications of Acanthamoeba and multiple potential opportunistic pathogens in roof-harvested rainwater tanks. Environ Res. 2016;150:320–7.PubMedCrossRefGoogle Scholar
  77. 77.
    Lim KY, Hamilton AJ, Jiang SC. Assessment of public health risk associated with viral contamination in harvested urban stormwater for domestic applications. Sci Total Environ. 2015;523:95–108.PubMedCrossRefGoogle Scholar
  78. 78.
    Jesmi Y, Rahiman KMM, Hatha AAM, Deepu L, Jyothi S. Risk assessment of rooftop-collected rainwater for individual household and community use in central Kerala, India. J Environ Health. 2014;76(6):114–21.PubMedGoogle Scholar
  79. 79.
    Oscar TP. Risk of Salmonellosis from chicken parts prepared from whole chickens sold in flow pack wrappers and subjected to temperature abuse. J Food Prot. 2017;80(9):1496–505.PubMedCrossRefGoogle Scholar
  80. 80.
    Maffei DF, Sant’Ana AS, Franco BDGM, Schaffner DW. Quantitative assessment of the impact of cross-contamination during the washing step of ready-to-eat leafy greens on the risk of illness caused by Salmonella. Food Res Int. 2017;92:106–12.PubMedCrossRefGoogle Scholar
  81. 81.
    Swart AN, van Leusden F, Nauta MJ. A QMRA model for Salmonella in pork products during preparation and consumption. Risk Anal. 2016;36(3):516–30.PubMedCrossRefGoogle Scholar
  82. 82.
    Finger F, Genolet T, Mari L, de Magny GC, Manga NM, Rinaldo A, et al. Mobile phone data highlights the role of mass gatherings in the spreading of cholera outbreaks. Proc Natl Acad Sci. 2016;113(23):6421–6.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Mari L, Bertuzzo E, Finger F, Casagrandi R, Gatto M, Rinaldo A. On the predictive ability of mechanistic models for the Haitian cholera epidemic. J R Soc Interface. 2015;12(104):20140840.PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Kirpich A, Weppelmann TA, Yang Y, Ali A, Morris JG, Longini IM. Cholera Transmission in Ouest Department of Haiti: Dynamic Modeling and the Future of the Epidemic. PLoS Negl Trop Dis. 2015;9(10):1–12.CrossRefGoogle Scholar
  85. 85.
    Mukandavire Z, Morris JG. Modeling the epidemiology of cholera to prevent disease transmission in developing Countries. Microbiol Spectr. 2015;3(3):898264.CrossRefGoogle Scholar
  86. 86.
    Njagarah JBH, Nyabadza F. Modelling Optimal Control of Cholera in Communities Linked by Migration. Comput Math Methods Med. 2015;2015Google Scholar
  87. 87.
    Collins OC, Govinder KS. Incorporating heterogeneity into the transmission dynamics of a waterborne disease model. J Theor Biol. 2014;356:133–43.PubMedCrossRefGoogle Scholar
  88. 88.
    Yang J, Qiu Z, Li XZ. Global stability of an age-structured cholera model. Math Biosci Eng. 2014;11(3):641–65.PubMedCrossRefGoogle Scholar
  89. 89.
    Kong JD, Davis W, Wang H. Dynamics of a cholera transmission model with immunological threshold and natural phage control in reservoir. Bull Math Biol. 2014;76(8):2025–51.PubMedCrossRefGoogle Scholar
  90. 90.
    Sardar T, Mukhopadhyay S, Bhowmick AR, Chattopadhyay J. An optimal cost effectiveness study on Zimbabwe cholera seasonal data from 2008-2011. PLoS One. 2013;8(12):e81231.PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Eisenberg MC, Shuai Z, Tien JH, van den Driessche P. A cholera model in a patchy environment with water and human movement. Math Biosci. 2013;246(1):105–12.PubMedCrossRefGoogle Scholar
  92. 92.
    Rinaldo A, Bertuzzo E, Mari L, Righetto L, Blokesch M, Gatto M, et al. Reassessment of the 2010-2011 Haiti cholera outbreak and rainfall-driven multiseason projections. Proc Natl Acad Sci. 2012;109(17):6602–7.PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Righetto L, Casagrandi R, Bertuzzo E, Mari L, Gatto M, Rodriguez-Iturbe I, et al. The role of aquatic reservoir fluctuations in long-term cholera patterns. Epidemics. 2012;4(1):33–42.PubMedCrossRefGoogle Scholar
  94. 94.
    Yaari R, Kaliner E, Grotto I, Katriel G, Moran-Gilad J, Sofer D, et al. Modeling the spread of polio in an IPV-vaccinated population: lessons learned from the 2013 silent outbreak in southern Israel. BMC Med. 2016;14(1):95.PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Famulare M. Has Wild poliovirus been eliminated from Nigeria? PLoS One. 2015;10(8):1–13.CrossRefGoogle Scholar
  96. 96.
    Blake IM, Martin R, Goel A, Khetsuriani N, Everts J, Wolff C, et al. The role of older children and adults in wild poliovirus transmission. Proc Natl Acad Sci. 2014;111(29):10604–9.PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Kim JH, Mogasale V, Burgess C, Wierzba TF. Impact of oral cholera vaccines in cholera-endemic countries: A mathematical modeling study. Vaccine. 2016;34(18):2113–20.PubMedCrossRefGoogle Scholar
  98. 98.
    Azman AS, Luquero FJ, Ciglenecki I, Grais RF, Sack DA, Lessler J. The impact of a one-dose versus two-dose oral cholera vaccine regimen in outbreak settings: A modeling study. PLoS Med. 2015;12(8):1–18.CrossRefGoogle Scholar
  99. 99.
    Posny D, Wang J, Mukandavire Z, Modnak C. Analyzing transmission dynamics of cholera with public health interventions. Math Biosci. 2015;264(1):38–53.PubMedCrossRefGoogle Scholar
  100. 100.
    Dimitrov DT, Troeger C, Halloran ME, Longini IM, Chao DL. Comparative effectiveness of different strategies of oral cholera vaccination in bangladesh: a modeling study. PLOS neglected tropical diseases. 2014; 8(12):e 3343.Google Scholar
  101. 101.
    Safi MA, Melesse DY, Gumel AB. Dynamics analysis of a multi-strain cholera model with an imperfect vaccine. Bull Math Biol. 2013;75(7):1104–37.PubMedCrossRefGoogle Scholar
  102. 102.
    Mukandavire Z, Smith DL, Morris JG. Cholera in Haiti: Reproductive numbers and vaccination coverage estimates. Sci Rep. 2013;3:997.PubMedPubMedCentralCrossRefGoogle Scholar
  103. 103.
    Dénes A, Székely L. Global dynamics of a mathematical model for the possible re-emergence of polio. Math Biosci. 2017;293:64–74.Google Scholar
  104. 104.
    Houy N. The case for periodic OPV routine vaccination campaigns. J Theor Biol. 2016;389:20–7.PubMedCrossRefGoogle Scholar
  105. 105.
    Thompson KM, Duintjer Tebbens RJ. The differential impact of oral poliovirus vaccine formulation choices on serotype-specific population immunity to poliovirus transmission. BMC Infect Dis. 2015;15(1):376.PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Wilder-Smith A, Leong WY, Lopez LF, Amaku M, Quam M, Khan K, et al. Potential for international spread of wild poliovirus via travelers. BMC Med. 2015;13(1):133.PubMedPubMedCentralCrossRefGoogle Scholar
  107. 107.
    Wagner BG, Behrend MR, Klein DJ, Upfill-Brown AM, Eckhoff PA, Quantifying HH. the impact of expanded age group campaigns for polio eradication. PLoS One. 2014;9(12):1–14.CrossRefGoogle Scholar
  108. 108.
    Duintjer Tebbens RJ, Kalkowska DA, Wassilak SG, Pallansch MA, Cochi SL, Thompson KM. The potential impact of expanding target age groups for polio immunization campaigns. BMC Infect Dis. 2014;14(1):45.PubMedPubMedCentralCrossRefGoogle Scholar
  109. 109.
    Hansen Edwards C, de Blasio BF, Salamanca BV, Flem E. Re-evaluation of the cost-effectiveness and effects of childhood rotavirus vaccination in Norway. PLoS One. 2017;12(8):e0183306.PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Bilcke J, Chapman R, Atchison C, Cromer D, Johnson H, Willem L, et al. Quantifying parameter and structural uncertainty of dynamic disease transmission models using MCMC: An application to rotavirus vaccination in England and Wales. Med Decis Mak. 2015;35(5):633–47.CrossRefGoogle Scholar
  111. 111.
    Pitzer VE, Bilcke J, Heylen E, Crawford FW, Callens M, De Smet F, et al. Did large-scale vaccination drive changes in the circulating rotavirus population in Belgium? Sci Rep. 2015;5:1–14.Google Scholar
  112. 112.
    Pitzer VE, Atkins KE, de Blasio BF, van Effelterre T, Atchison CJ, Harris JP, et al. Direct and indirect effects of rotavirus vaccination: Comparing predictions from transmission dynamic models. PLoS One. 2012;7(8)Google Scholar
  113. 113.
    Atkins KE, Shim E, Carroll S, Quilici S, Galvani AP. The cost-effectiveness of pentavalent rotavirus vaccination in England and Wales. Vaccine. 2012;30(48):6766–76.PubMedCrossRefGoogle Scholar
  114. 114.
    Bollerslev AM, Nauta M, Hansen TB, Aabo S. A risk modelling approach for setting microbiological limits using enterococci as indicator for growth potential of Salmonella in pork. Int J Food Microbiol. 2017;240:102–7.PubMedCrossRefGoogle Scholar
  115. 115.
    Snary EL, Swart AN, Simons RRL, Domingues ARC, Vigre H, Evers EG, et al. A Quantitative Microbiological Risk Assessment for Salmonella in Pigs for the European Union. Risk Anal. 2016;36(3):437–49.PubMedCrossRefGoogle Scholar
  116. 116.
    Vigre H, Barfoed K, Swart AN, Simons RRL, Hill AA, Snary EL, et al. Characterization of the Human Risk of Salmonellosis Related to Consumption of Pork Products in Different E.U. Countries Based on a QMRA. Risk Anal. 2016;36(3):531–45.PubMedCrossRefGoogle Scholar
  117. 117.
    Lee H, Kim K, Choi KH, Yoon Y. Quantitative microbial risk assessment for Staphylococcus aureus in natural and processed cheese in Korea. J Dairy Sci. 2015;98(9):5931–45.PubMedCrossRefGoogle Scholar
  118. 118.
    Jeong J, Lee J, Lee H, Lee S, Kim S, Ha J, et al. Quantitative microbial risk assessment for campylobacter foodborne illness in raw beef offal consumption in South Korea. J Food Prot. 2017;80(4):609–18.PubMedCrossRefGoogle Scholar
  119. 119.
    Kiermeier A, Jenson I, Sumner J. Risk assessment of Escherichia coli O157 illness from consumption of hamburgers in the United States made from Australian manufacturing beef. Risk Anal. 2015;35(1):77–89.PubMedCrossRefGoogle Scholar
  120. 120.
    Guillier L, Danan C, Bergis H, Delignette-Muller ML, Granier S, Rudelle S, et al. Use of quantitative microbial risk assessment when investigating foodborne illness outbreaks: The example of a monophasic Salmonella Typhimurium 4,5,12: I : - Outbreak implicating beef burgers. Int J Food Microbiol. 2013;166(3):471–8.PubMedCrossRefGoogle Scholar
  121. 121.
    Hurd HS, Malladi S. An outcomes model to evaluate risks and benefits of Escherichia coli vaccination in beef cattle. Foodborne Pathog Dis. 2012;9(10):952–61.PubMedPubMedCentralCrossRefGoogle Scholar
  122. 122.
    Smadi H, Sargeant JM. Quantitative risk assessment of human salmonellosis in Canadian broiler chicken breast from retail to consumption. Risk Anal. 2013;33(2):232–48.PubMedCrossRefGoogle Scholar
  123. 123.
    Boysen L, Nauta M, Duarte ASR, Rosenquist H. Human risk from thermotolerant Campylobacter on broiler meat in Denmark. Int J Food Microbiol. 2013;162(2):129–34.PubMedCrossRefGoogle Scholar
  124. 124.
    Signorini ML, Zbrun MV, Romero-Scharpen A, Olivero C, Bongiovanni F, Soto LP, et al. Quantitative risk assessment of human campylobacteriosis by consumption of salad cross-contaminated with thermophilic Campylobacter spp. from broiler meat in Argentina. Prev Vet Med. 2013;109(1-2):37–6.PubMedCrossRefGoogle Scholar
  125. 125.
    Smadi H, Sargeant JM. Review of Canadian Literature to Estimate Risks Associated with Salmonella in Broilers from Retail to Consumption in Canadian Homes. Crit Rev Food Sci Nutr. 2013;53(7):694–705.PubMedCrossRefGoogle Scholar
  126. 126.
    Thebault A, Le Saux JC, Pommepuy M, Le Guyader S, Lailler R, Denis JB. Quantitative approach of risk management strategies for hepatitis a virus-contaminated oyster production areas. J Food Prot. 2012;75(7):1249–57.PubMedCrossRefGoogle Scholar
  127. 127.
    Singer RS, Ruegg PL, Bauman DE. Quantitative risk assessment of antimicrobial-resistant foodborne infections in humans due to recombinant bovine somatotropin usage in dairy cows. J Food Prot. 2017;80(7):1099–116.PubMedCrossRefGoogle Scholar
  128. 128.
    Giacometti F, Bonilauri P, Piva S, Scavia G, Amatiste S, Bianchi DM, et al. Paediatric HUS Cases Related to the Consumption of Raw Milk Sold by Vending Machines in Italy: Quantitative Risk Assessment Based on Escherichia coli O157 Official Controls over 7 years. Zoonoses Public Health. 2016:505–16.Google Scholar
  129. 129.
    Giacometti F, Bonilauri P, Amatiste S, Arrigoni N, Bianchi M, Losio MN, et al. Human campylobacteriosis related to the consumption of raw milk sold by vending machines in Italy: Quantitative risk assessment based on official controls over four years. Prev Vet Med. 2015;121(1-2):151–8.PubMedCrossRefGoogle Scholar
  130. 130.
    Giacometti F, Bonilauri P, Albonetti S, Amatiste S, Arrigoni N, Bianchi M, et al. Quantitative risk assessment of human salmonellosis and listeriosis related to the consumption of raw milk in Italy. J Food Prot. 2015;78(1):13–21.PubMedCrossRefGoogle Scholar
  131. 131.
    Perrin F, Tenenhaus-Aziza F, Michel V, Miszczycha S, Bel N, Sanaa M. Quantitative risk assessment of haemolytic and uremic syndrome linked to O157: H7 and Non-O157: H7 shiga-toxin producing Escherichia coli strains in raw milk soft cheeses. Risk Anal. 2015;35(1):109–28.PubMedCrossRefGoogle Scholar
  132. 132.
    Pouillot R, Hoelzer K, Ramirez GA, DeGraft-Hanson J, Dennis SB. Assessment of the risk of salmonellosis from internally contaminated shell eggs following initial storage at 18°C (65°F), compared with 7°C (45°F). Food Microbiol. 2014;43:16–9.PubMedCrossRefGoogle Scholar
  133. 133.
    Giacometti F, Serraino A, Bonilauri P, Ostanello F, Daminelli P, Finazzi G, et al. Quantitative risk assessment of verocytotoxin producing Escherichia coli O157 and Campylobacter jejuni related to consumption of raw milk in a province in northern Italy. J Food Prot. 2012;75(11):2031–8.PubMedCrossRefGoogle Scholar
  134. 134.
    Lambertini E, Barouei J, Schaffner DW, Danyluk MD, Harris LJ. Modeling the risk of salmonellosis from consumption of pistachios produced and consumed in the United States. Food Microbiol. 2017;67:85–96.PubMedCrossRefGoogle Scholar
  135. 135.
    Pang H, Lambertini E, Buchanan RL, Schaffner DW, Pradhan AK. Quantitative microbial risk assessment for Escherichia coli O157:H7 in fresh-cut lettuce. J Food Prot. 2017;80(2):302–11.PubMedCrossRefGoogle Scholar
  136. 136.
    Bouwknegt M, Verhaelen K, Rzezutka A, Kozyra I, Maunula L, von Bonsdorff CH, et al. Quantitative farm-to-fork risk assessment model for norovirus and hepatitis A virus in European leafy green vegetable and berry fruit supply chains. Int J Food Microbiol. 2015;198:50–8.PubMedCrossRefGoogle Scholar
  137. 137.
    Pielaat A, van Leusden FM, Wijnands LM. Microbiological risk from minimally processed packaged salads in the Dutch food chain. J Food Prot. 2014;77(3):395–403.PubMedCrossRefGoogle Scholar
  138. 138.
    Soller JA, Schoen M, Steele JA, Griffith JF, Schiff KC. Incidence of gastrointestinal illness following wet weather recreational exposures: Harmonization of quantitative microbial risk assessment with an epidemiologic investigation of surfers. Water Res. 2017;121:280–9.PubMedCrossRefGoogle Scholar
  139. 139.
    Adell AD, McBride G, Wuertz S, Conrad PA, Smith WA. Comparison of human and southern sea otter (Enhydra lutris nereis) health risks for infection with protozoa in nearshore waters. Water Res. 2016;104:220–30.PubMedCrossRefGoogle Scholar
  140. 140.
    Eregno FE, Tryland I, Tjomsland T, Myrmel M, Robertson L, Heistad A. Quantitative microbial risk assessment combined with hydrodynamic modelling to estimate the public health risk associated with bathing after rainfall events. Sci Total Environ. 2016;548-549:270–9.PubMedCrossRefGoogle Scholar
  141. 141.
    Corsi SR, Borchardt MA, Carvin RB, Burch TR, Spencer SK, Lutz MA, et al. Human and bovine viruses and bacteria at three Great Lakes beaches: Environmental variable associations and health risk. Environ Sci Technol. 2016;50(2):987–95.PubMedCrossRefGoogle Scholar
  142. 142.
    Liao H, Krometis LAH, Kline K. Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed. Sci Total Environ. 2016;551-552:668–75.PubMedCrossRefGoogle Scholar
  143. 143.
    Vergara GGRV, Rose JB, Gin KYH. Risk assessment of noroviruses and human adenoviruses in recreational surface waters. Water Res. 2016;103:276–82.PubMedCrossRefGoogle Scholar
  144. 144.
    Sterk A, de Man H, Schijven JF, de Nijs T, de Roda Husman AM. Climate change impact on infection risks during bathing downstream of sewage emissions from CSOs or WWTPs. Water Res. 2016;105:11–21.PubMedCrossRefGoogle Scholar
  145. 145.
    Timm C, Luther S, Jurzik L, Hamza IA, Kistemann T. Applying QMRA and DALY to assess health risks from river bathing. Int J Hyg Environ Health. 2016;219(7:681–92.CrossRefGoogle Scholar
  146. 146.
    Jacob P, Henry A, Meheut G, Charni-Ben-Tabassi N, Ingr V, Helmi K. Health risk assessment related to waterborne pathogens from the river to the tap. Int J Environ Res Public Health. 2015;12(3):2967–83.PubMedPubMedCentralCrossRefGoogle Scholar
  147. 147.
    Prez VE, Gil PI, Temprana CF, Cuadrado PR, Martínez LC, Giordano MO, et al. Quantification of human infection risk caused by rotavirus in surface waters from Cordoba, Argentina. Sci Total Environ. 2015;538:220–9.PubMedCrossRefGoogle Scholar
  148. 148.
    Lodder WJ, Schijven JF, Rutjes SA, de Roda Husman AM, Teunis PFM. Entero- and parechovirus distributions in surface water and probabilities of exposure to these viruses during water recreation. Water Res. 2015;75:25–32.PubMedCrossRefGoogle Scholar
  149. 149.
    Soller JA, Schoen ME, Varghese A, Ichida AM, Boehm AB, Eftim S, et al. Human health risk implications of multiple sources of faecal indicator bacteria in a recreational waterbody. Water Res. 2014;66:254–64.PubMedCrossRefGoogle Scholar
  150. 150.
    Wilkes G, Brassard J, Edge TA, Gannon V, Jokinen CC, Jones TH, et al. Bacteria, viruses, and parasites in an intermittent stream protected from and exposed to pasturing cattle: Prevalence, densities, and quantitative microbial risk assessment. Water Res. 2013;47(16):6244–57.PubMedCrossRefGoogle Scholar
  151. 151.
    McBride GB, Stott R, Miller W, Bambic D, Wuertz S. Discharge-based QMRA for estimation of public health risks from exposure to stormwater-borne pathogens in recreational waters in the United States. Water Res. 2013;47(14):5282–97.PubMedCrossRefGoogle Scholar
  152. 152.
    Kundu A, McBride G, Wuertz S. Adenovirus-associated health risks for recreational activities in a multi-use coastal watershed based on site-specific quantitative microbial risk assessment. Water Res. 2013;47(16):6309–25.PubMedCrossRefGoogle Scholar
  153. 153.
    Schippmann B, Schernewski G, Grawe U. Escherichia coli pollution in a Baltic Sea lagoon: A model-based source and spatial¨ risk assessment. Int J Hyg Environ Health. 2013;216(4):408–20.PubMedCrossRefGoogle Scholar
  154. 154.
    Dickinson G, ying Lim K, Jiang SC. Quantitative microbial risk assessment of pathogenic vibrios in marine recreational waters of Southern California. Appl Environ Microbiol. 2013;79(1):294–302.PubMedPubMedCentralCrossRefGoogle Scholar
  155. 155.
    Sales-Ortells H, Medema G. Microbial health risks associated with exposure to stormwater in a water plaza. Water Res. 2015;74:34–46.PubMedCrossRefGoogle Scholar
  156. 156.
    Sales-Ortells H, Medema G. Screening-level microbial risk assessment of urban water locations: A tool for prioritization. Environ Sci Technol. 2014;48(16):9780–9.PubMedCrossRefGoogle Scholar
  157. 157.
    De Man H, Van Den Berg HHJL, Leenen EJTM, Schijven JF, Schets FM, Van Der Vliet JC, et al. Quantitative assessment of infection risk from exposure to waterborne pathogens in urban floodwater. Water Res. 2014;48(1):90–9.PubMedCrossRefGoogle Scholar
  158. 158.
    Suppes LM, Canales RA, Gerba CP, Reynolds KA. Cryptosporidium risk from swimming pool exposures. Int J Hyg Environ Health. 2016;219(8):915–9.PubMedCrossRefGoogle Scholar
  159. 159.
    De Man H, Bouwknegt M, van Heijnsbergen E, Leenen EJTM, van Knapen F, de Roda Husman AM. Health risk assessment for splash parks that use rainwater as source water. Water Res. 2014;54:254–61.PubMedCrossRefGoogle Scholar
  160. 160.
    Barker SF, Packer M, Scales PJ, Gray S, Snape I, Hamilton AJ. Pathogen reduction requirements for direct potable reuse in Antarctica: Evaluating human health risks in small communities. Sci Total Environ. 2013;461-462:723–33.PubMedCrossRefGoogle Scholar
  161. 161.
    Hoyer AB, Schladow SG, Rueda FJ. A hydrodynamics-based approach to evaluating the risk of waterborne pathogens entering drinking water intakes in a large, stratified lake. Water Res. 2015;83:227–36.PubMedCrossRefGoogle Scholar
  162. 162.
    Raslan R, El Sayegh S, Chams S, Chams N, Leone A, Hajj Hussein I. Re-emerging vaccine-preventable diseases in war-affected peoples of the eastern Mediterranean region—An update. Front Public Health. 2017;5:1–8.CrossRefGoogle Scholar
  163. 163.
    Bartak R, Page D, Sandhu C, Grischek T, Saini B, Mehrotra I, et al. Application of risk-based assessment and management to riverbank filtration sites in India. J Water Health. 2015;13(1):174–89.PubMedCrossRefGoogle Scholar
  164. 164.
    Chigor VN, Sibanda T, Okoh AI. Assessment of the risks for human health of adenoviruses, hepatitis A virus, rotaviruses and enteroviruses in the Buffalo River and three source water dams in the Eastern Cape. Food Environ Virol. 2014;6(2):87–98.PubMedCrossRefGoogle Scholar
  165. 165.
    Sato MIZ, Galvani AT, Padula JA, Nardocci AC, Lauretto MS, Razzolini MTP, et al. Assessing the infection risk of Giardia and Cryptosporidium in public drinking water delivered by surface water systems in Sao Paulo State, Brazil. Sci Total Environ. 2013;442:389–96.PubMedCrossRefGoogle Scholar
  166. 166.
    An W, Zhang D, Xiao S, Yu J, Yang M. Risk assessment of Giardia in rivers of southern China based on continuous monitoring. J Environ Sci. 2012;24(2):309–13.CrossRefGoogle Scholar
  167. 167.
    Balderrama-Carmona AP, Gortáres-Moroyoqui P, Álvarez-Valencia LH, Castro-Espinoza L, Balderas-Cortés JDJ, Mondaca-Fernández I, et al. Quantitative microbial risk assessment of Cryptosporidium and Giardia in well water from a native community´ of Mexico. Int J Environ Health Res 2015; 25(5):570–582.Google Scholar
  168. 168.
    Shrestha S, Haramoto E, Malla R, Nishida K. Risk of diarrhoea from shallow groundwater contaminated with enteropathogens in the Kathmandu Valley, Nepal. J Water Health. 2015;13(1):259–69.PubMedCrossRefGoogle Scholar
  169. 169.
    Xiao S, An W, Chen Z, Zhang D, Yu J, Yang M. The burden of drinking water-associated cryptosporidiosis in China: The large contribution of the immunodeficient population identified by quantitative microbial risk assessment. Water Res. 2012;46(13):4272–80.PubMedCrossRefGoogle Scholar
  170. 170.
    Thomas K, McBean E, Shantz A, Murphy HM. Comparing the microbial risks associated with household drinking water supplies used in peri-urban communities of Phnom Penh, Cambodia. J Water Health. 2015;13(1):243–58.PubMedCrossRefGoogle Scholar
  171. 171.
    Machdar E, van der Steen NP, Raschid-Sally L, Lens PNL. Application of Quantitative Microbial Risk Assessment to analyze the public health risk from poor drinking water quality in a low income area in Accra, Ghana. Sci Total Environ. 2013;449:134–42.PubMedCrossRefGoogle Scholar
  172. 172.
    Bivins AW, Sumner T, Kumpel E, Howard G, Cumming O, Ross I, et al. Estimating Infection Risks and the Global Burden of Diarrheal Disease Attributable to Intermittent Water Supply Using QMRA. Environ Sci Technol. 2017;51(13):7542–51.PubMedCrossRefGoogle Scholar
  173. 173.
    Enger KS, Nelson KL, Clasen T, Rose JB, Eisenberg JNS. Linking quantitative microbial risk assessment and epidemiological data: Informing safe drinking water trials in developing countries. Environ Sci Technol. 2012;46(9):5160–7.PubMedCrossRefGoogle Scholar
  174. 174.
    Ferrer A, Nguyen-Viet H, Zinsstag J. Quantification of diarrhea risk related to wastewater contact in Thailand. EcoHealth. 2012;9(1):49–59.PubMedCrossRefGoogle Scholar
  175. 175.
    Gao T, Chen R, Wang X, Ngo HH, Li YY, Zhou J, et al. Application of disease burden to quantitative assessment of health hazards for a decentralized water reuse system. Sci Total Environ. 2016;551-552(13):83–91.PubMedCrossRefGoogle Scholar
  176. 176.
    Koepke AA, Longini IM, Halloran ME, Wakefield J, Minin VN. Predictive modeling of cholera outbreaks in Bangladesh. Ann Appl Stat. 2016;10(2):575–95.PubMedPubMedCentralCrossRefGoogle Scholar
  177. 177.
    Fung ICH. Cholera transmission dynamic models for public health practitioners. Emerging Themes Epidemiol 2014;11(1):1.Google Scholar
  178. 178.
    Okosun KO, Makinde OD. A co-infection model of malaria and cholera diseases with optimal control. Math Biosci. 2014;258:19–32.PubMedCrossRefGoogle Scholar
  179. 179.
    Misra AK, Singh V. A delay mathematical model for the spread and control of water borne diseases. J Theor Biol. 2012;301:49–56.PubMedCrossRefGoogle Scholar
  180. 180.
    Kim JH, Rho SH. Transmission dynamics of oral polio vaccine viruses and vaccine-derived polioviruses on networks. J Theor Biol. 2015;364:266–74.PubMedCrossRefGoogle Scholar
  181. 181.
    Kisjes KH, Tebbens RJD, Wallace GS, Pallansch MA, Cochi SL, Wassilak SGF, et al. Individual-based modeling of potential poliovirus transmission in connected religious communities in North America with low uptake of vaccination. J Infect Dis. 2014;210(Suppl 1):S424–33.PubMedCrossRefGoogle Scholar
  182. 182.
    Mayer BT, Eisenberg JNS, Henry CJ, Gomes MGM, Ionides EL, Koopman JS. Successes and shortcomings of polio eradication: A transmission modeling analysis. Am J Epidemiol. 2013;177(11):1236–45.PubMedPubMedCentralCrossRefGoogle Scholar
  183. 183.
    Duintjer Tebbens RJ, Pallansch MA, Kalkowska DA, Wassilak SGF, Cochi SL, Thompson KM. Characterizing poliovirus transmission and evolution: Insights from modeling experiences with wild and vaccine-related polioviruses. Risk Anal. 2013;33(4):703–49.PubMedCrossRefGoogle Scholar
  184. 184.
    Thompson KM, Wallace GS, Tebbens RJD, Smith PJ, Barskey AE, Pallansch MA, et al. Trends in the risk of U.S. polio outbreaks and poliovirus vaccine availability for response. Public Health Rep. 2012;127(1):23–37.PubMedPubMedCentralCrossRefGoogle Scholar
  185. 185.
    Martinez PP, King AA, Yunus M, Faruque ASG, Pascual M. Differential and enhanced response to climate forcing in diarrheal disease due to rotavirus across a megacity of the developing world. Proc Natl Acad Sci. 2016;113(15):4092–7.PubMedPubMedCentralCrossRefGoogle Scholar
  186. 186.
    Van Effelterre T, Guignard A, Marano C, Rojas R, Jacobsen KH. Modeling the hepatitis A epidemiological transition in Brazil and Mexico. Human Vaccines Immunotherapeutics. 2017;13(8):1942–51.PubMedPubMedCentralCrossRefGoogle Scholar
  187. 187.
    Van Effelterre T, Marano C, Jacobsen KH. Modeling the hepatitis A epidemiological transition in Thailand. Vaccine. 2016;34(4):555–62.PubMedCrossRefGoogle Scholar
  188. 188.
    Curran D, de Ridder M, Van Effelterre T. The impact of assumptions regarding vaccine-induced immunity on the public health and cost-effectiveness of hepatitis A vaccination: Is one dose sufficient? Human Vaccines Immunotherapeutics. 2016;12(11):2765–71.PubMedPubMedCentralCrossRefGoogle Scholar
  189. 189.
    Dhankhar P, Nwankwo C, Pillsbury M, Lauschke A, Goveia MG, Acosta CJ, et al. Public health impact and cost-effectiveness of hepatitis A vaccination in the United States: A disease transmission dynamic modeling approach. Value Health. 2015;18(4):358–67.PubMedCrossRefGoogle Scholar
  190. 190.
    Van Effelterre T, De Antonio-Suarez R, Cassidy A, Romano-Mazzotti L, Marano C. Model-based projections of the population-level impact of hepatitis A vaccination in Mexico. Human Vaccines Immunotherapeutics. 2012;8(8):1099–108.PubMedPubMedCentralCrossRefGoogle Scholar
  191. 191.
    Saad NJ, Bowles CC, Grenfell BT, Basnyat B, Arjyal A, Dongol S, et al. The impact of migration and antimicrobial resistance on the transmission dynamics of typhoid fever in Kathmandu, Nepal: A mathematical modelling study. PLoS Negl Trop Dis. 2017;11(5):1–16.CrossRefGoogle Scholar
  192. 192.
    Tilahun GT, Makinde OD, Malonza D. Modelling and optimal control of pneumonia disease with cost-effective strategies. J Biol Dyn. 2017;11:400–26.PubMedCrossRefGoogle Scholar
  193. 193.
    • Pitzer VE, Feasey NA, Msefula C, Mallewa J, Kennedy N, Dube Q, et al. Mathematical modeling to assess the drivers of the recent emergence of typhoid fever in Blantyre, Malawi. Clin Infect Dis. 2015;61(Suppl 4):S251–8. This IDTM analysis uses a compartmental model with an environmental reservoir to make clinically relevant conclusions about the role of drug resistance in recent Typhoid fever outbreaks. PubMedPubMedCentralCrossRefGoogle Scholar
  194. 194.
    Miura F, Watanabe T, Watanabe K, Takemoto K, Fukushi K. Comparative assessment of primary and secondary infection risks in a norovirus outbreak using a household model simulation. J Environ Sci (China). 2016;50:13–20.CrossRefGoogle Scholar
  195. 195.
    Lopman B, Simmons K, Gambhir M, Vinjé J, Parashar U. Epidemiologic implications of asymptomatic reinfection: A mathematical modeling study of norovirus. Am J Epidemiol. 2014;179(4):507–12.Google Scholar
  196. 196.
    MIilbrath MO, Spicknall IH, Zelner JL, Moe CL, Eisenberg JNS. Heterogeneity in norovirus shedding duration affects community risk. Epidemiol Infect. 2013;141(08):1572–84.CrossRefGoogle Scholar
  197. 197.
    Snedeker KG, Shaw DJ, Locking ME, Prescott RJ. Primary and secondary cases in Escherichia coli O157 outbreaks: A statistical analysis. BMC Infect Dis. 2009;9:144.PubMedPubMedCentralCrossRefGoogle Scholar
  198. 198.
    for Disease Control USC, Prevention. 2017 – Outbreaks of hepatitis A in multiple states among people who are homeless and people who use drugs; 2017. Available from: Scholar
  199. 199.
    Mari L, Bertuzzo E, Righetto L, Casagrandi R, Gatto M, Rodriguez-Iturbe I, et al. Modelling cholera epidemics: The role of waterways, human mobility and sanitation. J R Soc Interface. 2012;(67):376–88.Google Scholar
  200. 200.
    Gatto M, Mari L, Bertuzzo E, Casagrandi R, Righetto L, Rodriguez-Iturbe I, et al. Spatially explicit conditions for waterborne pathogen invasion. Am Nat. 2013;182(3):328–46.PubMedCrossRefGoogle Scholar
  201. 201.
    • Brouwer AF, Weir MH, Eisenberg MC, Meza R, Eisenberg JNS. Dose-response relationships for environmentally mediated infectious disease transmission models. PLOS Comput Biol. 2017;13(4):1–28. This methodological analysis incorporates QMRA dose-response functions into IDT models with environmental compartments. CrossRefGoogle Scholar
  202. 202.
    Liu J, Gratz J, Amour C, Kibiki G, Becker S, Janaki L, et al. A laboratory-developed Taqman Array Card for simultaneous detection of 19 enteropathogens. J Clin Microbiol. 2013;51(2):472–80.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Andrew F. Brouwer
    • 1
  • Nina B. Masters
    • 1
  • Joseph N. S. Eisenberg
    • 1
  1. 1.Department of EpidemiologyUniversity of MichiganAnn ArborUSA

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