Abstract
This study evaluated the results recorded at the Central Public Health Laboratory of Santa Catarina state (Brazil) concerning the investigation of Rotavirus (RVA) and Norovirus (NoVs) – genogroups GI and GII. Samples were taken from seawater, river water, estuary water, lagoon water, and treated water samples, from 2018 to 2021. The aim was to correlate them with each other and evaluate their association with the type of water, presence of shellfish farming, population density, and sewage treatment. The most prevalent enteric virus was RVA, followed by NoV GI and NoV GII. There was a strong correlation between the presence/absence of RVA and the presence/absence of at least one NoV genogroup, mainly in samples collected in rivers. No correlation was observed between the presence of any virus and the presence of shellfish farming. When evaluating the binomial sewage treatment vs. population density, the correlation coefficients between population density and the presence of the virus in a sample were higher than the coefficients between the percentage of treated sewage and the presence of the virus. Sources of human-origin pollution impair the quality of treated and surface waters, and therefore the results of this work can help develop viral-monitoring programs in these places.
HIGHLIGHTS
Rotavirus (RVA) and Norovirus GI and GII (NoVs) were present in 42 and 44% of the analyzed samples, respectively.
The most prevalent virus was RVA (42.3%), followed by NoV GI (22.90%) and NoV GII (22.3%).
No association was observed between the presence of RVA and NoVs and the presence of shellfish farming.
An association between population density, treated sewage, and the presence of RVA and NoVs was observed.
INTRODUCTION
The investigation of viruses in treated and untreated water is a relevant line of inquiry in development worldwide. In Brazil and many other countries, this control has been based on the research of fecal indicator microorganisms (thermotolerant coliforms, Escherichia coli, and enterococci). However, there is no correlation between bacterial contamination and the presence of enteric viruses (Qiu et al. 2015). Viruses of fecal origin, such as Rotavirus (RVA) and Norovirus (NoVs), can be isolated from surface water sources, and several studies have already shown that their presence can compromise the quality of drinking water (Fongaro et al. 2015; Shi et al. 2021).
According to Pang et al. (2019), surface waters can be contaminated by effluents from water and sewage treatment plants. Even with the dilution of viral particles, there is still a risk to public health due to its low infective dose. Despite reducing virus concentration during treatment processes, many enteric viruses can remain infectious. Some of them can resist the treatments applied in bacterial control, including chlorination, and this can lead to outbreaks of enteric diseases, resulting from the consumption of water with accepted values of coliform standards but with a detectable result for enteric viruses (Fongaro et al. 2015; Qiu et al. 2015; Salvador et al. 2020). The quality of food produced in water, such as bivalve mollusks, can also be harmed by discharging waste into surface waters or improper treatment. Its consumption in nature is a worrying factor since they are filter feeders and can accumulate contaminants present in water (Suplicy 2018).
This study aimed to survey the results recorded in the analysis management system of the Central Public Health Laboratory of Santa Catarina state from Brazil (GAL/LACEN/SC) concerning research on RVA and NoVs (genogroups GI and GII) in water samples of river, sea, estuary, lagoon, and treated water, in the period between 2018 and 2021, to correlate them with the type of water, presence of mollusk farming sites, population density, and sewage treatment.
MATERIALS AND METHODS
Collection and reception of samples
A total of 170 samples of river, sea, estuary, lagoon, and treated water (well water and water from collective and individual supply systems) were collected from 16 municipalities in Santa Catarina state (Florianópolis, Itapema, Balneário Camboriú, Porto Belo, Bombinhas, Governador Celso Ramos, Itajaí, São João do Oeste, Canelinha, Irineópolis, Orleans, Água Doce, Guaraciaba, Princesa, Santa Rosa do Sul, and Urussanga) for the research of RVA and NoVs (genogroups GI and GII). The collections took place in 2018 (January, March, August, October, and December), 2019 (January, February, March, November, and December), 2020 (January, February, and December), and 2021 (January, February, and March). A volume of 2 L was collected per sample, which was transported and refrigerated in the laboratory and analyzed within 48 h after collection.
Surface water samples (river, sea, estuary, and lagoon) were part of the ‘Veraneio’, a monitoring program instituted by a partnership between the Santa Catarina state Health Surveillance Board (DIVS/SC) and Central Public Health Laboratory of Santa Catarina (LACEN/SC). In addition, samples of treated water from supply systems (municipal or individual) were analyzed to investigate a suspected outbreak of waterborne disease (OWD). Table 1 presents the number of samples collected in each municipality, considering the aquatic matrix and the year of analysis.
Number of samples collected per year in each municipality and aquatic matrix
Collected aquatic matrix . | City of origin . | Number of samples . | |||
---|---|---|---|---|---|
2018 . | 2019 . | 2020 . | 2021 . | ||
Potable water n = 26 | Água Doce | 1 | – | – | – |
Canelinha | – | 3 | – | – | |
Florianópolis | 4 | 3 | – | – | |
Guaraciaba | 1 | – | – | – | |
Irineópolis | 1 | – | – | 1 | |
Itajaí | 4 | – | – | – | |
Orleans | – | – | 2 | – | |
Princesa | 1 | – | – | – | |
Santa Rosa do Sul | 1 | – | – | – | |
São João do Oeste | 3 | – | – | – | |
Urussanga | – | – | – | 1 | |
Seawater n = 50 | Balneário Camboriú | – | – | 1 | 3 |
Bombinhas | – | – | 3 | 9 | |
Florianópolis | – | 13 | 5 | – | |
Governador Celso Ramos | – | – | 1 | 3 | |
Itapema | – | 4 | 2 | 6 | |
River water n = 80 | Balneário Camboriú | – | 2 | 2 | 6 |
Florianópolis | – | 32 | 11 | – | |
Governador Celso Ramos | – | – | 2 | 6 | |
Itapema | – | 2 | 1 | 3 | |
Porto Belo | – | 1 | 3 | 9 | |
Estuary water n = 9 | Florianópolis | – | 7 | 2 | – |
Lagoon water n = 5 | Florianópolis | – | 3 | 2 | – |
Collected aquatic matrix . | City of origin . | Number of samples . | |||
---|---|---|---|---|---|
2018 . | 2019 . | 2020 . | 2021 . | ||
Potable water n = 26 | Água Doce | 1 | – | – | – |
Canelinha | – | 3 | – | – | |
Florianópolis | 4 | 3 | – | – | |
Guaraciaba | 1 | – | – | – | |
Irineópolis | 1 | – | – | 1 | |
Itajaí | 4 | – | – | – | |
Orleans | – | – | 2 | – | |
Princesa | 1 | – | – | – | |
Santa Rosa do Sul | 1 | – | – | – | |
São João do Oeste | 3 | – | – | – | |
Urussanga | – | – | – | 1 | |
Seawater n = 50 | Balneário Camboriú | – | – | 1 | 3 |
Bombinhas | – | – | 3 | 9 | |
Florianópolis | – | 13 | 5 | – | |
Governador Celso Ramos | – | – | 1 | 3 | |
Itapema | – | 4 | 2 | 6 | |
River water n = 80 | Balneário Camboriú | – | 2 | 2 | 6 |
Florianópolis | – | 32 | 11 | – | |
Governador Celso Ramos | – | – | 2 | 6 | |
Itapema | – | 2 | 1 | 3 | |
Porto Belo | – | 1 | 3 | 9 | |
Estuary water n = 9 | Florianópolis | – | 7 | 2 | – |
Lagoon water n = 5 | Florianópolis | – | 3 | 2 | – |
Concentration of viral particles
The methodology used for the concentration was described by Katayama et al. (2002), based on the adsorption–elution method, followed by centrifugation. It is worth mentioning that, regardless of the aquatic matrix, the method used to concentrate and elute the viral particles was the same due to the availability of such methodology in LACEN/SC. The internal viral control was the bacteriophage PP7, used to ensure viral particle recovery. To facilitate adherence of viral particles to the filtration membrane, 2 L of the sample was treated with 2 M MgCl2 (Exodo Científica, Brazil) and subsequently acidified to pH 3.5 with 6 N HCl (Reagen, Colombo, PR, Brazil). After adding the internal control, the sample was filtered through a negatively charged HA® membrane (0.45-μm pores, 90 mm in diameter, Millipore, Bedford, MA, USA), attached to a Millipore® filtration system. The membrane was washed with 0.5 mM H2SO4 solution (Darmstadt, Germany). To elute the viral particles, the membrane was placed in a Petri dish (diameter 160 mm) containing 3 mM NaOH (Neon Comercial, Suzano, SP, Brazil) and shaken in an orbital shaker (Kasvi, São José dos Pinhais, PR, Brazil). The volume was aspirated, placed in a Centriprep® Millipore YM-50 concentrator, neutralized with 50 mM H2SO4 and Tris–EDTA buffer (Sigma–Aldrich, St. Louis, MO, USA), and centrifuged at 1.500 rpm for 10 min at 4 °C (Sigma, Ostrode, Germany).
Extraction of viral RNA and preparation of complementary DNA (cDNA)
The extraction and purification of viral RNA were performed from the concentrated suspension using a QIAamp Viral RNA Mini – QIAGEN® extraction kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. To enable detection by Reverse Transcription followed by Quantitative Polymerase Chain Reaction (RT-qPCR), the extracted RNA was added to a mix containing random primers and reverse transcriptase (RT) enzyme to synthesize the cDNA. This mixture was placed in a thermocycler (Eppendorf®, Hamburg, Germany) and subjected to 25 °C for 5 min, 50 °C for 1 h, 70 °C for 20 min, and 10 °C for 45 cycles. The material produced was stored in an ultra-freezer (−80 °C).
Detection of RVA and NoVs (GI and GII) by RT-qPCR
The reaction conditions were defined according to the instructions of the reagent used (GoTaq Master Mix®, Promega, Madison, WI, USA). First, 7 μL of DNAse and RNAse-free ultrapure water, 10 μL of Master Mix, 1 μL of each primer, and 1 μL of the probe were mixed and distributed into the wells of an optical PCR microplate (Axygen®, Union City, CA, USA), with 20 μL per well. Then, 5 μL of the cDNA was added to the wells. The microplate was sealed with optical adhesive (MicroAmp®, Applied Biosystems, Foster City, CA, USA), centrifuged, and placed into the ABI7500 RT-qPCR instrument (Applied Biosystems).
The reaction conditions for the RVA investigation were as follows: 95 °C for 2 min, followed by 45 cycles of denaturation at 95 °C for 15 min, annealing and extension at 60 °C for 1 min. To search for NoVs, the same conditions were used, except for the annealing step, which took place at 56 °C for 30 s. Each reaction was performed in duplicate. The negative control was ultrapure water free of RNAse, and the positive controls were plasmids of PP7, RVA, NoVs GI, and GII. Table 2 presents the sequences of the primers and probes used.
Primers and probes used in RT-qPCR reactions for RVA and NoVs (GI and GII)
. | Primers and probes . | Sequence 5′–3′ . | Reaction concentration (μM) . | References . |
---|---|---|---|---|
RVA | RVA-F | AACATCTWCACRTRACCCTCTATGAG | 0.4 | Zeng et al. (2008) |
RVA-R | GGTCACATAACGCCCCTATAGC | 0.4 | ||
RVA-S | VIC-AGTTAAAAGCTAACACTGTCAAA–MGB | 0.2 | ||
NoV GI | Cog 1-F | CGYTGGATGCGNTTYCATGA | 0.6 | Kageyama et al. (2003) |
Cog 1-R | CTTAGACGCCATCATCATTYAC | 0.6 | ||
Sonda ring 1 cog 1 | FAM-AGATYGCGATCYCCTGTCCA-TAMRA | 0.3 | ||
NoV GII | Cog 2-F | CARGARBCNATGTTYAGRTGGATGAG | 0.6 | Kageyama et al. (2003) |
Cog 2-R | TCGACGCCATCTTCATTCACA | 0.6 | ||
Sonda ring 2 cog 2 | VIC-TGGGAGGGCGATCGCAATCT-MGBNFQ | 0.3 |
. | Primers and probes . | Sequence 5′–3′ . | Reaction concentration (μM) . | References . |
---|---|---|---|---|
RVA | RVA-F | AACATCTWCACRTRACCCTCTATGAG | 0.4 | Zeng et al. (2008) |
RVA-R | GGTCACATAACGCCCCTATAGC | 0.4 | ||
RVA-S | VIC-AGTTAAAAGCTAACACTGTCAAA–MGB | 0.2 | ||
NoV GI | Cog 1-F | CGYTGGATGCGNTTYCATGA | 0.6 | Kageyama et al. (2003) |
Cog 1-R | CTTAGACGCCATCATCATTYAC | 0.6 | ||
Sonda ring 1 cog 1 | FAM-AGATYGCGATCYCCTGTCCA-TAMRA | 0.3 | ||
NoV GII | Cog 2-F | CARGARBCNATGTTYAGRTGGATGAG | 0.6 | Kageyama et al. (2003) |
Cog 2-R | TCGACGCCATCTTCATTCACA | 0.6 | ||
Sonda ring 2 cog 2 | VIC-TGGGAGGGCGATCGCAATCT-MGBNFQ | 0.3 |
After researching RVA and NoVs (GI and GII), the results were registered in the GAL/LACEN/SC, a system developed for Brazilian Public Health Laboratories, and nationally standardized by the Ministry of Health (MH).
Data collection
To verify the correlation with the viruses isolated in the water samples of the present study, bibliographic research was carried out to gather information on the presence of sewage treatment systems in the municipalities where the collections took place, the presence of malacoculture activity nearby to the collection points, and the population density of the cities. The database of the Brazilian Institute of Geography and Statistics (BIGS) was the basis for surveying the population density of each city, as well as for verifying the presence/absence of sewage treatment at collection sites. The document ‘Strategic Plan for the Sustainable Development of Mariculture in Santa Catarina 2018–2028’ (Suplicy 2018) supported the research of regions with the presence of mariculture activity and production of bivalve mollusks.
Statistical analysis
The year 2018 was not included in the statistical analysis due to insufficient data. The results obtained in the other years of the study (2019, 2020, and 2021) were statistically analyzed using Pearson's chi-square independence test (χ²) and contingency coefficient as a measure of association between qualitative variables and the calculation of Pearson's correlation in the quantitative ones, with a significance level of 5%. The software used was JAMOVI, version 1.6.23.
RESULTS
In 2018, 16 treated water samples were analyzed to confirm OWD from eight municipalities in Santa Catarina. In 2019, 70 samples were collected in five municipalities: 37 from the river, 17 from the sea, 7 from the estuary, 3 from the lagoon, and 6 from treated water. In 2020, samples were collected in 7 municipalities, with a total of 37 samples, where 19 were river water, 12 were seawater, 2 were estuary water, 2 were lagoon water, and 2 were treated water. Finally, in 2021, 47 samples were collected in seven municipalities: 24 from the river, 21 from the sea, and 2 from treated water.
Table 3 presents the number of samples analyzed, the samples detected for one or both viruses researched in each type of water, and the municipalities included in the study. Florianópolis was the municipality with the highest number of collections (n = 82); in 52% (n = 43) of these, one or both targets were identified.
Global results for each municipality during the years 2018–2021
City . | No. of samples . | No. (%) of positive samplesa . | No. of positive samples/total number of samples by water type . | ||||
---|---|---|---|---|---|---|---|
River . | Sea . | Estuary . | Lagoon . | Treated . | |||
Florianópolis | 82 | 43 (52%) | 31/43 | 11/18 | 1/9 | 0/5 | 0/7 |
Itapema | 18 | 11 (61%) | 4/6 | 7/12 | – | – | – |
Balneário Camboriú | 14 | 10 (71%) | 9/10 | 1/4 | – | – | – |
Porto Belo | 13 | 6 (46%) | 6/13 | – | – | – | – |
Bombinhas | 12 | 5 (41%) | – | 5/12 | – | – | – |
Gov. Celso Ramos | 12 | 7 (58%) | 3/8 | 4/4 | – | – | – |
Itajaí | 4 | 0 (0%) | – | – | – | – | 0/4 |
São João do Oeste | 3 | 0 (0%) | – | – | – | – | 0/3 |
Canelinha | 3 | 0 (0%) | – | – | – | – | 0/3 |
Irineópolis | 2 | 0 (0%) | – | – | – | – | 0/2 |
Orleans | 2 | 1 (50%) | – | – | – | – | 1/2 |
Água Doce | 1 | 0 (0%) | – | – | – | – | 0/1 |
Guaraciaba | 1 | 0 (0%) | – | – | – | – | 0/1 |
Princesa | 1 | 0 (0%) | – | – | – | – | 0/1 |
Santa Rosa do Sul | 1 | 1 (100%) | – | – | – | – | 1/1 |
Urussanga | 1 | 0 (0%) | – | – | – | – | 0/1 |
Total | 170 | 84 (49%) | 53/80 | 28/50 | 1/9 | 0/5 | 2/26 |
City . | No. of samples . | No. (%) of positive samplesa . | No. of positive samples/total number of samples by water type . | ||||
---|---|---|---|---|---|---|---|
River . | Sea . | Estuary . | Lagoon . | Treated . | |||
Florianópolis | 82 | 43 (52%) | 31/43 | 11/18 | 1/9 | 0/5 | 0/7 |
Itapema | 18 | 11 (61%) | 4/6 | 7/12 | – | – | – |
Balneário Camboriú | 14 | 10 (71%) | 9/10 | 1/4 | – | – | – |
Porto Belo | 13 | 6 (46%) | 6/13 | – | – | – | – |
Bombinhas | 12 | 5 (41%) | – | 5/12 | – | – | – |
Gov. Celso Ramos | 12 | 7 (58%) | 3/8 | 4/4 | – | – | – |
Itajaí | 4 | 0 (0%) | – | – | – | – | 0/4 |
São João do Oeste | 3 | 0 (0%) | – | – | – | – | 0/3 |
Canelinha | 3 | 0 (0%) | – | – | – | – | 0/3 |
Irineópolis | 2 | 0 (0%) | – | – | – | – | 0/2 |
Orleans | 2 | 1 (50%) | – | – | – | – | 1/2 |
Água Doce | 1 | 0 (0%) | – | – | – | – | 0/1 |
Guaraciaba | 1 | 0 (0%) | – | – | – | – | 0/1 |
Princesa | 1 | 0 (0%) | – | – | – | – | 0/1 |
Santa Rosa do Sul | 1 | 1 (100%) | – | – | – | – | 1/1 |
Urussanga | 1 | 0 (0%) | – | – | – | – | 0/1 |
Total | 170 | 84 (49%) | 53/80 | 28/50 | 1/9 | 0/5 | 2/26 |
aNumber of samples positive for one or both viruses investigated.
In 2018, 93.7% of the samples showed an undetected result. In 2019, 50% of the results were undetectable, 40.5 and 44.8% in 2020 and 2021, respectively. Within the evaluation period, 2019 was the year in which more collections (n = 70) and 50% (n = 35) showed some detectable results. Of this amount (n = 35), 94% corresponded to RVA, 31% to NoV GI, and 34% to NoV GII. Significant detections also occurred in 2021, when 47 samples were analyzed with 45% (n = 21) of detectable results and with higher detection of NoV GI and NoV GII, 81% for both (n = 17). RVA represented 95% of detections in that year (n = 20).
Graphic representation of positive samples from 2019 to 2021, organized by the type of water in Florianópolis; Balneário Camboriú; Itapema; Bombinhas; Porto Belo; Governador Celso Ramos.
Graphic representation of positive samples from 2019 to 2021, organized by the type of water in Florianópolis; Balneário Camboriú; Itapema; Bombinhas; Porto Belo; Governador Celso Ramos.
Prevalence map of positive samples in Santa Catarina municipalities regarding the detection of RVA, NoV GI and NoV GII.
Prevalence map of positive samples in Santa Catarina municipalities regarding the detection of RVA, NoV GI and NoV GII.
DISCUSSION
The occurrence of enteric viruses in wastewater has been studied for many years and remains a threat to public health worldwide, related not only to the effectiveness of water and sewage treatment but also to the consumption of food cultivated in contaminated aquatic environments. The growing and uncontrolled occupation of urban areas is a reality in many countries, which means a challenge to the basic sanitation structure. This facilitates the contamination of water sources by insufficiently treated effluents or inadequate sewage connections. In Santa Catarina state, this scenario is no different (Fongaro et al. 2015; Garbossa et al. 2016; Suplicy 2018). This research analyzed data from river, sea, estuary, lagoon, and treated water samples collected in six municipalities. These municipalities present a significant increase in population during the summer season.
The most prevalent enteric virus in the 170 samples analyzed was RVA (42.3%), followed by NoV GI (22.90%) and NoV GII (22.3%). The predominance of RVA in samples could be justified by the presence of strains of vaccine origin in the studied environments. Since 2006, the Human RVA Oral Vaccine (VORH) has been included in the National Immunization Program for all children under 6 months. Future studies must confirm this hypothesis to differentiate between wild RVA and vaccine RVA strains.
In the set of samples that made up this study, it was found that there is a strong association between the presence/absence of RVA and the presence/absence of at least one NoV (p < 0.001; contingency coefficient = 0.393). The presence of RVA and at least one NoV is associated in all samples from Florianópolis (p < 0.001) and from Balneário Camboriú (p < 0.007). The results of samples from Itapema did not indicate dependence between these viruses (p = 0.705), as well as those collected in Bombinhas (p = 0.295), Governador Celso Ramos (p = 0.480), and Porto Belo (p = 0.640). The existence of an association between the presence of RVA and NoVs in the analyzed samples is an important finding since both are the leading causes of outbreaks of gastroenteritis transmitted by water ingestion worldwide (Shi et al. 2021) and are not yet considered in legislation as quality parameters to be monitored. Shi et al. (2021) also found a correlation between the presence of RVA and NoV GII in an urban river in Tianjin (China) and their prevalence in human feces samples and suggest that the investigation of these two viruses can serve to monitor the prevalence of human enteric viruses in the local population. La Rosa et al. (2017) demonstrated that NoVs are among the most detected viruses in the Tiber River, but RVA is less common there.
In Brazil, OWD are classified as Public Health Events (PHE) and are part of the national list of diseases that must be notified by the MH. From 2012 to 2021, 25.2% of these outbreaks were due to the consumption of contaminated water, with 5.2 and 4.4% being caused by NoV and RVA, respectively (Brasil 2022a). According to the epidemiological bulletin (Brasil 2022b), from 2016 to 2019, 541 (21.6%) of the 2,504 cases of outbreaks had the etiological agents identified, with NoV and RVA listed among the most prevalent, representing 8.3 and 6.9%, respectively. According to the MH, OWD notification registry database, from 2007 to 2021, seven cases of outbreaks involving these enteric viruses were cataloged, two of them caused by the ingestion of contaminated water. Table 4 shows the year in which this information was recorded, as well as the locations, the agent identified, and the product consumed by the affected people. There is an emphasis on the occurrence documented in 2018 from Santa Rosa do Sul, which corresponds to one of the detections carried out at LACEN/SC that year and mentioned earlier in this work.
Cases of OWD involving viruses registered in Santa Catarina state from 2007 to 2021
Year of registration . | City . | Agent . | Place of occurrence . | Product consumed . |
---|---|---|---|---|
2010 | Balneário Camboriú | Norovirus | Asylum | Sweets and desserts |
2011 | Jaraguá do Sul | Norovirus | Other Institutions | Water |
2013 | Caibi | Norovirus | Daycare/School | Ignored |
2013 | Chapecó | Rotavirus | Scattered cases | Ignored |
2017 | Florianópolis | Norovirus | Daycare/School | Mixed foods |
2018 | Santa Rosa do Sul | Norovirus | Daycare/School | Water |
2019 | Florianópolis | Norovirus | Residence | Inconclusive |
Year of registration . | City . | Agent . | Place of occurrence . | Product consumed . |
---|---|---|---|---|
2010 | Balneário Camboriú | Norovirus | Asylum | Sweets and desserts |
2011 | Jaraguá do Sul | Norovirus | Other Institutions | Water |
2013 | Caibi | Norovirus | Daycare/School | Ignored |
2013 | Chapecó | Rotavirus | Scattered cases | Ignored |
2017 | Florianópolis | Norovirus | Daycare/School | Mixed foods |
2018 | Santa Rosa do Sul | Norovirus | Daycare/School | Water |
2019 | Florianópolis | Norovirus | Residence | Inconclusive |
When considering the type of water analyzed, the statistical analysis, presented in Table 5, revealed that there is an association between the presence of RVA and at least one NoV in the samples from the river. Samples of marine water proved to be independent regarding the occurrence of these viruses. The presence of NoV GI and NoV GII is associated both in the river and marine samples.
Association between the detected viruses considering the aquatic matrix and the year of sample collection
Type of water | River n = 80 | RVA and NoV GI or NoV GII | + | p < 0.001; cc = 0.4266 |
RVA and NoV GI | + | p < 0.001 | ||
NoV GI and GII | + | p < 0.001 | ||
RVA and NoV GII | + | p < 0.001 | ||
Marine n = 50 | RVA and NoV GI or NoV GII | − | p = 1.000 | |
RVA and NoV GI | − | p = 0.518 | ||
NoV GI and GII | + | p = 0.003 | ||
RVA and NoV GII | − | p = 0.526 | ||
Year | 2019 n = 70 | RVA and NoV GI or NoV GII | + | p < 0.001; cc = 0.403 |
RVA and NoV GI | + | p = 0.002; cc = 0.354 | ||
NoV GI and NoV GII | + | p < 0.001 | ||
RVA and NoV GII | − | p = 0.131 | ||
2020 n = 37 | RVA and NoV GI or NoV GII | + | p = 0.022; cc = 0.352 | |
RVA and NoV GI | + | p = 0.016; cc = 0.369 | ||
NoV GI and NoV GII | + | p = 0.002 | ||
RVA and NoV GII | − | p = 0.131 | ||
2021 n = 47 | RVA and NoV GI or NoV GII | + | p = 0.003; cc = 0.396 | |
RVA and NoV GI | + | p < 0.001; cc = 0.401 | ||
NoV GI and NoV GII | + | p < 0.001 | ||
RVA and NoV GII | − | p = 0.131 |
Type of water | River n = 80 | RVA and NoV GI or NoV GII | + | p < 0.001; cc = 0.4266 |
RVA and NoV GI | + | p < 0.001 | ||
NoV GI and GII | + | p < 0.001 | ||
RVA and NoV GII | + | p < 0.001 | ||
Marine n = 50 | RVA and NoV GI or NoV GII | − | p = 1.000 | |
RVA and NoV GI | − | p = 0.518 | ||
NoV GI and GII | + | p = 0.003 | ||
RVA and NoV GII | − | p = 0.526 | ||
Year | 2019 n = 70 | RVA and NoV GI or NoV GII | + | p < 0.001; cc = 0.403 |
RVA and NoV GI | + | p = 0.002; cc = 0.354 | ||
NoV GI and NoV GII | + | p < 0.001 | ||
RVA and NoV GII | − | p = 0.131 | ||
2020 n = 37 | RVA and NoV GI or NoV GII | + | p = 0.022; cc = 0.352 | |
RVA and NoV GI | + | p = 0.016; cc = 0.369 | ||
NoV GI and NoV GII | + | p = 0.002 | ||
RVA and NoV GII | − | p = 0.131 | ||
2021 n = 47 | RVA and NoV GI or NoV GII | + | p = 0.003; cc = 0.396 | |
RVA and NoV GI | + | p < 0.001; cc = 0.401 | ||
NoV GI and NoV GII | + | p < 0.001 | ||
RVA and NoV GII | − | p = 0.131 |
(+), Positive association; (−), Negative association; p, probability value; c, contingency coefficient.
Considering the year of collection, there is an association between RVA and at least one NoV in the samples collected in 2019, as well as in the samples of 2020 and 2021. The same conclusion was observed when considering the relationship between RVA and NoV GI and between NoV GI and NoV GII in these periods. As for RVA and NoV GII, the analysis did not indicate an association between them in the years 2019, 2020, and 2021 (Table 5).
The municipalities of Florianópolis, Balneário Camboriú, Itapema, Bombinhas, Porto Belo, and Governador Celso Ramos are bivalve mollusks producers which emphasize the importance of water quality in these areas. As filter-feeding organisms, they can accumulate microorganisms present in the surrounding water. Therefore, the safety of those products is directly related to the sanitary conditions of the environment where they are grown. The maintenance of marine environmental quality is essential for the consolidation of this sector in that region, notably considering that Santa Catarina state is the major producer of bivalve mollusks in Brazil, accounting for 95% of national production (Suplicy 2018). It is worth noting that the microbiological standard for classifying bivalve mollusk farming areas in Brazil is the E. coli counts in bivalves (Brasil 2012), even though NoVs are among the enteric viruses most frequently related to disease episodes associated with the consumption of contaminated bivalve mollusks.
According to Campos et al. (2015), controlling gastroenteritis caused by NoVs, related to the consumption of contaminated mollusks, involves knowing the fate of these agents in the marine environment. They monitored human NoVs in oysters and water off the south coast of England impacted by sewage pollution but found no relationship between NoV contamination in oysters and tidal flows, as all samples tested were positive for both NoV GI and GII. In Florianópolis, some studies have already evaluated the presence of RVA and NoVs in seawater samples and mollusks. RVA was detected in 19% of the water samples analyzed by Rigotto et al. (2010) and was also the second most prevalent in cockle samples evaluated from November 2014 to April 2016 (Souza et al. 2018). Victoria et al. (2009) found detectable results for NoVs, with a prevalence of genogroup GII (68%) in marine water samples collected between 2007 and 2008. Another study evaluated the level of contamination of mariculture areas, resulting in the detection of NOVs GII both in the collected water samples and in those of mollusks (Souza et al. 2012). Both NoV GI and GII were found in seawater samples in a survey by Moresco et al. 2012. For the 144 seawater samples analyzed in this study, no association was observed between the presence of RVA, NoV GI and GII and the presence of shellfish farming (p < 0.001).
As human activity increases, so does the negative impact on water quality of water resources. La Rosa et al. (2017) concluded that there is a correlation between human pressure and the virological water quality of the Tiber River in Italy, as they detected an increase in river contamination as it flows from untouched areas to areas with agricultural, industrial, and urban activity. Garbossa et al. (2016) evaluated the load of thermotolerant coliforms present in the rivers that drained to the North and South Bays of the island of Santa Catarina and concluded that its increase is associated with the rise in the number of people residing in the place, as well as the population density and the percentage of the urbanized area. In addition, they found that basins that had more than 60% of the area covered by sewage treatment had higher loads of total coliforms per inhabitant than those with less than 25% coverage. They concluded that current sewage infrastructure could not effectively reduce fecal contamination, impairing the control of microbiological outbreaks from contact with recreational and shellfish farming waters. The statistical analysis of this work indicated that there is an association between population density and the presence of RVA (p = 0.027) and NoV GI and GII (p = 0.035).
Map relating the places where there is sewage treatment and the results showing the detection of RVA, NoV GI and NoV GII.
Map relating the places where there is sewage treatment and the results showing the detection of RVA, NoV GI and NoV GII.
Although 100% of the population has its sewage collected and treated, conventional treatment, consisting of the use of activated sludge, stabilization ponds, and biological filters, is not enough to remove the viral load (Qiu et al. 2015; Salvador et al. 2020) In Santa Catarina state it is common to have sewage collection through rainwater networks since 51 municipalities in Santa Catarina (11.5%) (BIGS 2020) declared that this practice occurs in their territory, which may justify the detectable results even in places with sewage treatment since that type of collection can contaminate surface water sources (Pang et al. 2019). Table 6 presents the general data of the municipalities where the sample was collected for this work, based on data released by the BIGS for the estimated population for the year 2021 and adequate sanitary sewage, that is, sewage collection, followed by treatment and use of a septic tank.
Sanitation indicators of some municipalities in Santa Catarina according to the last demographic census (2010)
City . | Estimated population – number of inhabitants . | Adequate sanitary sewage (%) . |
---|---|---|
Florianópolis | 516,624 | 87.8 |
Balneário Camboriú | 149,227 | 98.7 |
Itapema | 69,323 | 86.6 |
Porto Belo | 22,466 | 76.6 |
Bombinhas | 20,889 | 94.2 |
Governador Celso Ramos | 14,739 | 74.8 |
City . | Estimated population – number of inhabitants . | Adequate sanitary sewage (%) . |
---|---|---|
Florianópolis | 516,624 | 87.8 |
Balneário Camboriú | 149,227 | 98.7 |
Itapema | 69,323 | 86.6 |
Porto Belo | 22,466 | 76.6 |
Bombinhas | 20,889 | 94.2 |
Governador Celso Ramos | 14,739 | 74.8 |
Finally, considering the binomial sewage treatment vs. population density, statistical analysis was applied to verify its correlation with the proportion of detectable samples. In the case of proportion of samples with virus vs percentage of treated sewage, the correlation is moderate to strongly positive (RVA r = 0.765, p = 0.076; NoV GI r = 0.691, p = 0.128; NoV GII r = 0.646, p = 0.166; NoV GI or GII r = 0.549, p = 0.259). In the case of proportion of samples with virus vs population density, the correlation is strongly positive (RVA r = 0.935, p = 0.003; NoV GI r = 0.991, p ≤ 0 .001; NoV GII r = 0.969, p ≤ 0 .001; NoV GI or GII r = 0.927, p = 0.004). The analysis concluded that for the data collected in this study, the correlation coefficients between population density and the presence of the virus in a sample are greater than the correlation coefficients between the percentage of treated sewage and the presence of the virus in a sample. The sources of pollution of human origin are the main causes of the worsening of the quality of surface waters, mainly in areas used for mariculture (Souza et al. 2022). Therefore, investment in infrastructure and monitoring of these locations are essential.
CONCLUSIONS
This work demonstrated the presence of RVA and NoVs in 42 and 44% of the analyzed samples, respectively. In river samples, there is an association between the presence of these two viruses, an important finding that can evidence the insufficiency of the sanitary infrastructure or the undue dumping of untreated sewage in this source. As for the sea samples, the correlation between RVA and NoVs was not observed, and there was also no relationship between the detections and the presence of malacoculture areas. Despite this, of the 50 marine water samples, 28 were positive for any targets surveyed, revealing the need for more comprehensive monitoring in these areas. Considering that the microbiological quality of surface waters reflects the health status of the population, RVA and NoVs are among the main causative agents of OWD and that their detection in surface waters may show inadequate sewage disposal, the inclusion of its monitoring in outbreak contingency plans should be urgently considered by public health agencies.
ACKNOWLEDGEMENTS
The authors thank the Central Public Health Laboratory (LACEN/SC) for making the data available and Marcus Vinicius Duarte Rodrigues from the Laboratory of Applied Virology (UFSC).
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.