Case Study 3: Emerging & Zoonotic Pathogens

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Toxoplasma gondii in Brazil

Team Members: Escalante, A.E., Rigotto, C., Vereen, E., Kinyua, M., Delgado, M.F.

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Why is Toxoplasma considered an emerging pathogen? The ubiquitous protozoan Toxoplasma gondii is now the subject of renewed interest, due to the spread of oocysts through water causing outbreaks of toxoplasmosis in different parts of the world.

Infection with the Toxoplasma gondii is one of the most common parasitic infections in humans and other warm-blooded animals. Brazil has a very high rate of T. gondii infection in humans. Up to 50% of elementary school children and 50–80% of women of child-bearing age have antibodies to T. gondii (1). In most adults it does not cause serious illness, but blindness and mental retardation can result in congenitally infected children and severe disease in those with depressed immunity. Toxoplasmosis, until recently, was not considered a water-borne zoonosis, however it has been reported in many marine mammals.

In recent years, major outbreaks of toxoplasmosis have increased recognition of the risks of waterborne transmission of the environmentally resistant oocyst stage of T. gondii (2, 3).

Brazil is a large country with a human population of more than 190 million, and a booming economy. The seroprevalence of T. gondii was (and still is, (4)) 4 times (56% versus 13%) higher in Brazil than in the USA, and the magnitude of antibody titres were also higher (27% versus 1% at a titre of 1:256) in Brazil than in the USA. One of the largest outbreaks of clinical toxoplasmosis occurred in Santa Isabel do Ivaí Paraná with peaked between November 2001 and January 2002. This outbreak was epidemiologically linked to a cistern that supplied municipal water. Viable T. gondii was isolated from water tanks on roof tops that temporarily stored water (5). Problem formulation Since children are the most susceptible population, what is the risk of infection by Toxoplasma gondii through drinking water in Brazil?


Anthropogenic activities, in particular, reshape landscapes, climate, and species distributions and interactions across the globe, with significant potential to alter patterns of pathogen emergence and spread. Habitat conversion, introduction of non-native species, and increased contact between human, domestic animals, and wildlife populations have been linked to emerging viral, bacterial, and parasitic diseases. Climate change also has the potential to alter cycles of disease transmission by influencing vector and host ranges, pathogen survival, and dynamics of water-borne transmission. Of the 1415 organisms documented as human pathogens, over 60% are believed to have come from domestic or wild animal reservoirs (6).

Toxoplasma gondii, a globally distributed, zoonotic, protozoan parasite capable of infecting a wide range of warm-blooded animals. T. gondii is capable of infecting people from different ethnic groups and in both sexes worldwide making it one of the most “successful” protozoan parasites on earth. Infections in healthy adults and healthy children are usually asymptomatic; however, severe disease can occur in immunocompomised individuals and newborns. Congenital infection may occur following maternal infection during pregnancy. The severity of the disease may depend upon the stage of pregnancy at the time of infection. A wide spectrum of clinical disease occurs in congenitally infected children. Mild disease may consist of slightly diminished vision only whereas severely diseased children may have the full tetrad of signs including retinochoroiditis, hydrocephalus, convulsions, and intracerebral calcification (7).


Environmental transmission – oocyst loading and transport from terrestrial to aquatic systems:

Transmission of toxoplasmosis occurs by consumption of undercooked or raw meat containing tissue cysts, or by ingestion of resistant oocysts from environmental sources (soil, water, fruits and vegetables). Determination of sources of infection is technically difficult because by the time T. gondii infection is diagnosed the original source of infection may not be demonstrable. Oocysts, the exceptionally hardy free-living environmental stage of the parasite, play a key role in transmission of T. gondii to newly recognized hosts and ecosystems. As wild and domestic felids are the only known hosts (Figure 1) capable of shedding T. gondii oocysts in their feces (8).

Oocysts-life-cycle-casestudy32013.gif

Figure 1: Unsporulated oocysts are shed in the cat’s feces (1). Intermediate hosts in nature (including birds and rodents) become infected after ingesting soil, water or plant material contaminated with oocysts (2). Oocysts transform into tachyzoites localized in neural and muscle tissue and develop into tissue cyst bradyzoites (3). Cats become infected after consuming intermediate hosts harboring tissue cysts (4). Cats may also become infected directly by ingestion of sporulated oocysts. Animals bred for human consumption become infected after ingestion of sporulated oocysts in the environment (5). Humans can become infected by any of several routes: eating undercooked meat of animals harboring tissue cysts (6), consuming food or water contaminated with cat feces or by contaminated environmental samples (such as fecal-contaminated soil or changing the litter box of a pet cat) (7), blood transfusion or organ transplantation (8). transplacentally from mother to fetus (9). diagnosis is usually achieved by serology, although tissue cysts may be observed in stained biopsy specimens (10). Diagnosis of congenital infections can be achieved by detecting T. gondii DNA in amniotic fluid using molecular methods such as PCR (11). Adapted from CDC (http://www.cdc.gov/parasites/toxoplasmosis/biology.html)

The likelihood of oocyst shedding in a given location is influenced by felid distribution, availability of prey or other food resources, and human management of domestic and wild felid populations. Considering T. gondii environmental transmission in the context of felid distribution and oocyst shedding, as well as human landscape and animal management decisions, will facilitate identification and management of high-risk areas for parasite exposure. Transport and potential accumulation of T. gondii oocysts in environmental matrices, such as soil or water, is determined by felid behavior, environmental attributes, and oocyst surface properties. In addition to affecting sporulation and survival, felid defecation behaviors can alter the number of oocysts that can be entrained and transported in freshwater flow (6). The presence of T. gondii oocysts in water is only a health concern if the parasite remains infectious to susceptible hosts. Persistence of T. gondii in terrestrial and aquatic environments is closely governed by climatic factors. Humid environments and cooler temperatures are generally more favorable for oocyst survival (9).

Detection Methods:

There is no rapid detection method for T. gondii oocysts recovered from water or other environmental samples. Traditionally, the detection of protozoa in water required their concentration from large volumes of water by filtration or centrifugation, isolation from concentrated particulates by immunomagnetic separation (IMS) or other methods, and detection by immunofluorescence microscopy, molecular techniques, cell culture or combinations of these (10).


T. gondii oocysts in the environment

T. gondii oocyst concentration in source water is an assumption parameter extrapolated from studies looking at oocysts shed by cats in the environment as domestic and wild cats are the definitive host excreting T. gondii oocyst in their feces (1-5). Humans and other animals are intermediate hosts that do not form oocysts (1, 4, 6). As the frequency and concentration of naturally infected cat oocyst shedding in the environment is variable and in many cases unknown (7), we used a triangular distribution to fit a mean and range of T. gondii oocyst deposition estimated for California, USA (5) (Table 1). We estimated the annual concentration of T. gondii oocyst in the terrestrial environment of Brazil using estimates for the land area of Brazil as found in Table 1.

T. gondii oocysts in runoff, travel time and decay rate

Runoff and decay of T. gondii oocyst in water is of relevance to the exposure assessment; however there was no readily available information for T. gondii. We used laboratory data information for the runoff of Cryptosporidium parvum cysts in overland flow (8) as a surrogate for T. gondii oocyst and for our decay estimate (Table 1). From the experimental range of overland flow in the surrogate study (8), we used the strongest intensity of precipitation and the corresponding runoff value. We used an estimated decay rate of C. parvum cyst per day and viability (percentage survival) fit to a log normal distribution as our surrogates for T. gondii (Table 1). For the assumption of oocyst travel time in the source water to the point of removal at a treatment utility or individual, we used a custom model to fit our estimates of the velocity and length of oocyst travel in the watershed area for Brazil (Table 1).

Drinking water treatment efficiency and ingestion rate

The removal efficiency of T. gondii oocyst by the conventional and advanced treatment processes was assumed using Cryptosporidium as a surrogate when reliable experiments and/or studies with T. gondii were not readily available (Table 2). Additionally a lognormal distribution for water ingestion rate in southeastern Brazil with mean and standard deviation (SD) of 0.44 L/day (SD 0.92 L/day) for children was assumed based on a recent study by Sato et al. (9).

Daily risk and dose response

The daily risk is a forecast of our model, and annual risk is calculated from the daily risk. The risk with treatment interventions is a combination of the daily risk and the amount of reduction that is possible.

The purpose of the exposure assessment is to determine the amount, or numbers of organisms that correspond to a single exposure (dose) or the total amount or number of organisms that constitute a set of exposures (10). Among the three main routes of exposure (ingestion of contaminated water, ingestion of contaminated food, and vertical maternofetal transmission), only the contaminated drinking water ingestion route was taken into consideration in this study as this is considered the main route of emerging pathogenesis.

Table 1.
Parameters to estimate the risk of ingesting Toxoplasma gondii oocyst in drinking water

Parameter description Value (range) Value (mean) Value (Standard Deviation) Units Assumptions References
Environmental deposition in land 94-4600 1844.75 3.3x10^6 oocysts/m2 Triangular distribution.
Data was collected from a publication where the number of Toxoplasma oocysts on land were counted. The study was in California, and counts went from 94 to 4600 oocysts/m2. We decided to use the lowest numbers, given that in Brazil there is more rain compared to California; therefore we assume a higher dilution factor.
(5)
Total area of oocyst deposition. This corresponds to the total land extension of Brazil and data is readily available 8.547x10^6 km2 Water Resources Management in Brazil Webpage
http://hidroweb.ana.gov.br/doc/WRMB/part2.htm
Land runoff by rain 1.38-2.16 1.704 0.134 percent Normal Distribution
We used laboratory data information for runoff of oocysts on land into water bodies based on precipitation intensity. This distribution estimate was used to calculate the intensity of runoff.
(11)
Watershed volume of Brazil. Was needed to have an estimate of the dilution factor of oocysts in drinking water 5.732-8.49x10^3 7.341x10^3 828.63 km3 Triangular distribution
We assumed that oocysts on land were getting into the water through runoff. It was important to consider the watershed volume to estimate the concentration of T. gondii oocyst in Brazilian waterbodies as we also assumed all watersheds are used as sources for drinking water.
(12)
Water Resources Management in Brazil Webpage:
http://hidroweb.ana.gov.br/doc/WRMB/part2.htm
Watershed travel time We estimated an approximate travel time (residence time) for the T. gondii oocyst in the Brazilian watershed. The calculation was based on research on the distribution of different rivers in the UK (13). Based on this distribution, and data on length (upstream-downstream distance) of six major rivers in Brazil (14), the residence time of the T. gondii oocysts was calculated for the Brazilian watershed. (15)
(14)
Decay rate 0.011-0.013 0.012 0.0295 oocysts/day Log Normal Distribution
We used data for the decay rate of Cryptosporidium oocysts in the water distribution system of New York.
(15)
(16)
Oocyst viability 7.4-43.7 23.8 33.1 percentage Log Normal Distribution
This is the percent of viable T. gondii oocyst present in the watershed.
(17)
Daily volume of drinking water per child in Brazil 0.44 0.92 liters/day Log Normal Distribution
We focused on the most vulnerable subpopulation in Brazil (children less than or 5 years old) for exposure. Also, the data for dose-response was estimated from an experimental study on young mice
(9)

Table 2.
Drinking water treatment efficiency for Toxoplasma gondii

Parameter description Value (range) Value (mean) Value (Standard Deviation) Units Assumptions References
UV treatment (4mJ/cm2)
Log removal
1.6-2.1 1.8 0.2 Log 10 (removal) Triangular distribution
Different intensities of UV treatment were used to disinfect water with toxoplasma oocyst in a study by Ware et al. (18). The study used 0 – 100 mJ/cm2 and > 4 mJ/cm2 had from 2 to 4 log10 removal.
(18)
Boiling treatment
Log removal
2.0-3.5 3 0.167 Log 10 (removal) Log Normal distribution
Experimental data for Cryptosporidium
(19)
Filtration
Log removal
2.9-6.1 4.5 0.49 Log 10 (removal) Normal Distribution
Different concentrations of T. gondii oocyst were measured using slow sand filters for disinfection. In all concentrations <1 oocysts was identified in the final water.
(20)
(21)


Data for dose response on humans infected with Toxoplasma gondii was not available, therefore dose response data was calculated based on a study on young mice that ingested different doses of Toxoplasma gondii (18). Using the data from (18) the best fit model was exponential as shown on Figure 1. K value was 0, 0263.

Best-fit-model-casestudy32013.png

Figure 1: Best fit model based on data from (18).

Dose-casestudy32013.png


Figure 2: Dose calculation based on data from (18).

Dose-senstivity-case study32013.png

Figure 3: Sensitivity of different parameters and their effect dose calculation.


Four risk scenarios were ran using the Crystalball software using the assumptions shown on Table 1 and Equations 1 to 9. The four risk scenarios included daily risk without treatment of water, daily risk using 4mJ/cm2 UV treatment, daily risk using filtration and daily risk using boiling. Figure 1 illustrates the steps followed using the equations to calculate the dose and daily risk based on the 4 scenarios. Refer to appendix section for images and values for the mean daily risk, dose and sensitivity results.

From the sensitivity data for the infectivity of the water (dose), the decay rate and length of the river are most likely to assist in decreasing the infectivity of the water. This is because as the rate of oocysts dying during transportation and the length of rivers increases, the probability of infectivity decreases.

This same trend is observed for the daily risk without treatment, and using the three forms of treatment (UV, filtration and boiling). Decay rate and length of the river both reduced the daily risk of ingesting water contaminated with T. gondii. Apart from decay rate and length of the river, each of the treatment methods reduced the risk of ingesting water contaminated with T. gondii.

In dose calculations the child ingestion rate, velocity, deposition on land, % of water runoff from rain and viability of oocysts increased the infectivity of the oocysts. This means that the more water a child drinks the probability of them been infected increases. The scenario was the same for the risk of ingesting contaminated water without treatment and the 3 forms of treatment, but ln k also increased the risk of ingesting contaminated water.


Steps-to-calculating-risk-based-on assumptions-casestudy32013.png

Figure 1: Steps followed to calculate dose and daily risk for the 4 scenarios.


Table 1.
Equations used to calculate dose and risk based on assumption in Table 1 in the Exposure Assessment Section

Parameter Equation used Equation number
Total oocysts on land Environmental deposition on land * Total area of Brazil
(oocysts)
Eq. 1
Oocysts in water due to rain Eq. 1 * Land runoff from rain
(oocysts)
Eq. 2
Concentration of oocysts in all of Brazil watershed Eq. 2 * Total watershed volume
(oocysts/L)
Eq. 3
Travel time of oocysts from point of shedding to point of collection Length of river (km) / Velocity (km/day)
(day)
Eq. 4
Concentration of oocysts in the watershed based on the decay rate Eq. 3 * EXP(-decay rate * Eq.4)
(oocysts/L)
Eq. 5
Dose Eq. 5 * oocysts viability * daily child ingestion rate
(oocysts/day)
Eq. 6
Daily risk 1 – EXP(-k * Eq.6)
(oocysts/day)
Eq. 7
Probability of removal 1 – 10^(log removal) Eq. 8
Daily risk with treatment 1 – EXP (-k * Eq.6 * Eq. 8)
(oocysts/day)
Note:each treatment method had a different log removal
Eq.9


Based on results of the risk assessment, risk of a child (< 5 year old) infection through ingestion of T. gondii oocyst in untreated drinking water is high (5.72 x 10-4). The risk of mortality due to T. gondii ingestion was not included in this risk analysis as we presumed that infection may be a stronger indicator of the emergent property of T. gondii in lesser developed countries. As mentioned in the hazard identification, seroprevalence of T. gondii was found to be 4 times higher in Brazil than in the USA (1). Serological prevalence of T. gondii in 450 children (from 0 to 15) screened in the lone state of Sao Paulo in Brazil ranged from 0% in 2 to 3 year olds to more than half (53.3%) in children < 1 year old (1). Seropositivity in infants <1 year old was attributed to antibodies transferred from their infected mother (1). Our risk analysis of infection through ingestion does not account for vertical transmission from an infected mother. Complicating potential analysis is that presently there is also no national reference laboratory for T. gondii testing in Brazil and we recommend this as a first response to better categorize the prevalence of T. gondii.

Our analysis also sought to evaluate any potential lowered risk of a child (< 5 year old) infection through ingestion of T. gondii oocysts in treated drinking water under conventional and advanced treatment strategies (Table 1). The treatment strategies investigated were ultraviolet light (4), boiling (2) and filtration (3) detailed in our exposure assessment and in the relevant literature.

Table 1.
Daily Risk values for drinking water scenarios with and without treatment

Mean Daily Risk (oocysts/day) Standard deviation
Risk without treatment 5.72E-04 1.55E-03
Risk with UV treatment 8.50E-06 2.35E-05
Risk with boiling 1.92E-07 5.41E-07
Risk with filtration 3.39E-08 1.56E-07

The most effective methods we found for inactivating T. gondii in drinking water supplies of Brazil were boiling and filtration with a 3-log and 4-log removal of oocysts, respectively. As a management strategy in developing countries we suggest implementation of filtration in urban areas and boiling in rural areas of drinking water at a minimum to increase the removal of T. gondii oocyst in drinking water. This would yield comparable removal efficiency as seen in studies for a similar protozoan (e.g. Cyrptosporidium).

As our risk analysis did not investigate directly a difference in househould treatment vs a water treatment plant, we still recommend that in developing and extremely rural areas where we anticipate that individuals will not be receiving piped drinking water, that household ingestion of drinking water include either boiling water; or where piped water is available and T. gondii concentration in the environment is still anticipated to be high, we recommend filtration. Future analysis should investigate a cost benefit analysis of employing these treatment strategies as we estimated the United States cost for boiling water to be $0.22 liters per person per day (USGS, http://ga.water.usgs.gov/edu/qa-home-percapita.html) and a recent study by Ryan et al. (3) found estimated a cost of $2.31 USD per person per day for a boil water order for Cryptosporidium removal in the United States.

Final recommendations to prevent T. gondii infection from water, especially for children, should consider avoidance of ingesting untreated water from streams, lakes, rivers or ponds as this is common in developing areas or rural areas where piped water is not available. As a communication strategy, we propose educational workshops as to the treatment strategies for T. gondii identification and implementation of sanitary conditions to prevent and limit T. gondii infection. This should include information as to restricting the access of cats to areas around drinking waters tanks, reservoirs, and/or source water areas for drinking water. We include this issue for information as cats are the definitive host for these protozoan pathogens and domestic and feral cats may be a large and undefined population in developing areas. Based on our risk assessment, public water supplies should include filtration as part of the treatment process and should be implemented in rural and developing areas.

Risk-without-treatment-casestudy32013.png

Figure 1: Risk of drinking water contaminated with Toxoplasma gondii without treatment.

Sensitivity-without-treatment-casestudy32013.png

Figure 2: Sensitivity of different parameters and their effect on drinking water contaminated with Toxoplasma gondii without treatment.

Risk-with-UV-treatment-casestudy32013.png

Figure 3: Risk of drinking water treated with 4mJ/cm2 UV to remove Toxoplasma gondii.

Sensitivity-with-UV-treatment-casestudy32013.png

Figure 4: Sensitivity of different parameters and their effect on drinking water treated with 4mJ/cm2 UV.

Risk-with-boiling-as-treatment-casestudy32013.png

Figure 5: Risk of drinking water treated by boiling to remove Toxoplasma gondii.

Sensitivity-with-boiling-as-treatment-casestudy32013.png

Figure 6: Sensitivity of different parameters and their effect on drinking water treated by boiling.

Risk-with-filtration-treatment-casestudy32013.png

Figure 7: Risk of drinking water treated through filtration to remove Toxoplasma gondii.

Sensitivity-with-filtration-treatment-casestudy32013.png

Figure 8: Sensitivity of different parameters and their effect on drinking water treated through filtration.

Hazard and Problem Identification

1.Dubey JP, Lago EG, Gennari SM, Su C, Jones JL. 2012. Toxoplasmosis in humans and animals in Brazil: high prevalence, high burden of disease, and epidemiology. Parasitology 139:1375-1424.


2.Dubey JP. 2004. Toxoplasmosis - a waterborne zoonosis. Vet Parasitol 126:57-72.


3.Sroka S, Bartelheimer N, Winter A, Heukelbach J, Ariza L, Ribeiro H, Oliveira FA, Queiroz AJ, Alencar C, Liesenfeld O. 2010. Prevalence and risk factors of toxoplasmosis among pregnant women in Fortaleza, Northeastern Brazil. Am J Trop Med Hyg 83:528-533.


4.Dubey JP. 2010. Toxoplasma gondii infections in chickens (Gallus domesticus): prevalence, clinical disease, diagnosis and public health significance. Zoonoses Public Health 57:60-73.


5.de Moura L, Bahia-Oliveira LM, Wada MY, Jones JL, Tuboi SH, Carmo EH, Ramalho WM, Camargo NJ, Trevisan R, Graça RM, da Silva AJ, Moura I, Dubey JP, Garrett DO. 2006. Waterborne toxoplasmosis, Brazil, from field to gene. Emerg Infect Dis 12:326-329.


6.Vanwormer E, Fritz H, Shapiro K, Mazet JA, Conrad PA. 2013. Molecules to modeling: Toxoplasma gondii oocysts at the human-animal-environment interface. Comp Immunol Microbiol Infect Dis 36:217-231.


7.Dubey JP, Navarro IT, Sreekumar C, Dahl E, Freire RL, Kawabata HH, Vianna MC, Kwok OC, Shen SK, Thulliez P, Lehmann T. 2004. Toxoplasma gondii infections in cats from Paraná, Brazil: seroprevalence, tissue distribution, and biologic and genetic characterization of isolates. J Parasitol 90:721-726.


8.Hutchison WM, Dunachie JF, Siim JC, Work K. 1969. Life cycle of toxoplasma gondii. Br Med J 4:806.


9.Frenkel JK, Ruiz A, Chinchilla M. 1975. Soil survival of toxoplasma oocysts in Kansas and Costa Rica. Am J Trop Med Hyg 24:439-443.


10.Yang W, Lindquist HD, Cama V, Schaefer FW, Villegas E, Fayer R, Lewis EJ, Feng Y, Xiao L. 2009. Detection of Toxoplasma gondii oocysts in water sample concentrates by real-time PCR. Appl Environ Microbiol 75:3477-3483.


Exposure Assessment, Dose-Response and Risk Characterization

1. Elmore SA, Jones JL, Conrad PA, Patton S, Lindsay DS, Dubey JP. 2010. Toxoplasma gondii: epidemiology, feline clinical aspects, and prevention. Trends Parasitol 26:190-196.


2. Dubey JP, Lago EG, Gennari SM, Su C, Jones JL. 2012. Toxoplasmosis in humans and animals in Brazil: high prevalence, high burden of disease, and epidemiology. Parasitology 139:1375-1424.


3. Jones JL, Dubey JP. 2012. Foodborne toxoplasmosis. Clin Infect Dis 55:845-851.


4. Dabritz H, Conrad P. 2010. Cats and Toxoplasma: implications for public health. Zoonoses and Public Health 57:34-52.


5. Dabritz HA, Miller MA, Atwill ER, Gardner IA, Leutenegger CM, Melli AC, Conrad PA. 2007. Detection of Toxoplasma gondii-like oocysts in cat feces and estimates of the environmental oocyst burden. J Am Vet Med Assoc 231:1676-1684.


6. Hill DE, Chirukandoth S, Dubey J. 2005. Biology and epidemiology of Toxoplasma gondii in man and animals. Animal Health Research Reviews 6:41-62.


7. Jones JL, Dubey JP. 2010. Waterborne toxoplasmosis--recent developments. Exp Parasitol 124:10-25.


8. Trask JR, Kalita PK, Kuhlenschmidt MS, Smith RD, Funk TL. 2004. Overland and Near-Surface Transport of from Vegetated and Nonvegetated Surfaces. Journal of environmental quality 33:984-993.


9. Sato MI, Galvani AT, Padula JA, Nardocci AC, Lauretto MeS, Razzolini MT, Hachich EM. 2013. 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 442:389-396.


10. Haas CN, Rose JB, Gerba CP. 1999. Quantitative microbial risk assessment. John Wiley & Sons.


11. Trask JR, Kalita PK, Kuhlenschmidt MS, Smith RD, Funk TL. 2004. Overland and near-surface transport of Cryptosporidium parvum from vegetated and nonvegetated surfaces. J Environ Qual 33:984-993.


12. Marengo JA. 2008. Water and Climate Change, p. 83, Estudios Avancados, vol. 22.


13. Guymer I. 2006. A National Database of Travel Time, Disperson and Methodologies for the Protection of River Abstractions.


14. Braga B, Reboucas AdC, Tundisi JG. 2006. Aquas doces no Brasil: capital ecológico, uso e conservacao.


15. Robertson LJ, Campbell AT, Smith HV. 1992. Survival of Cryptosporidium parvum oocysts under various environmental pressures. Appl Environ Microbiol 58:3494-3500.


16. Walker F, Stedinger J. 1999. Fate and transport model of Cryptosporidium, p. 984-993, Journal of Environmental Quality, vol. 33.


17. Lélu M, Villena I, Dardé ML, Aubert D, Geers R, Dupuis E, Marnef F, Poulle ML, Gotteland C, Dumètre A, Gilot-Fromont E. 2012. Quantitative estimation of the viability of Toxoplasma gondii oocysts in soil. Appl Environ Microbiol 78:5127-5132.


18. Ware MW, Augustine SA, Erisman DO, See MJ, Wymer L, Hayes SL, Dubey JP, Villegas EN. 2010. Determining UV inactivation of Toxoplasma gondii oocysts by using cell culture and a mouse bioassay. Appl Environ Microbiol 76:5140-5147.


19. Ryan M, Gurian P, Haas C, Rose J, Duzinski P. 2013. Acceptable microbial risk: Cost-benefit analysis of a boil water order for Cryptosporidium, Journal of the American Water Works Association.


20. Cummins E, Kennedy R, Cormican M. 2010. Quantitative risk assessment of Cryptosporidium in tap water in Ireland, p. 740-753, Science of the Total Environment, vol. 408.


21. Timms S, Slade J, Fricker C. 1995. Removal of Cryptosporidium by Slow Sand Filtration, p. 81-84, Water Science and Technology, vol. 3.

Risk management

1.Dubey JP, Lago EG, Gennari SM, Su C, Jones JL. 2012. Toxoplasmosis in humans and animals in Brazil: high prevalence, high burden of disease, and epidemiology. Parasitology 139:1375-1424.


2.Ware MW, Augustine SA, Erisman DO, See MJ, Wymer L, Hayes SL, Dubey JP, Villegas EN. 2010. Determining UV inactivation of Toxoplasma gondii oocysts by using cell culture and a mouse bioassay. Appl Environ Microbiol 76:5140-5147.


3.Ryan M, Gurian P, Haas C, Rose J, Duzinski P. 2013. Acceptable microbial risk: Cost-benefit analysis of a boil water order for Cryptosporidium, Journal of the American Water Works Association.


4.Timms S, Slade J, Fricker C. 1995. Removal of Cryptosporidium by Slow Sand Filtration, p. 81-84, Water Science and Technology, vol. 3.