key: cord-0933920-4fmp2hz5
authors: Coronado, Y.; Navarro, R.; Mosqueda, C.; Valenzuela, V.; Perez, J. P.; Gonzalez-Mendoza, V.; De la Torre, M.; Rocha, J.
title: SARS-CoV-2 in wastewater from Mexico City used for irrigation in the Mezquital Valley: quantification and modelling of geographic dispersion
date: 2021-06-12
journal: nan
DOI: 10.1101/2021.06.07.21258522
sha: 014fa526667e263287366c110510d105e08c622b
doc_id: 933920
cord_uid: 4fmp2hz5

Quantification of SARS-CoV-2 in urban wastewaters has emerged as a cheap, efficient strategy to follow trends of active COVID-19 cases in populations. Moreover, mathematical models have been developed that allow prediction of active cases following the temporal patterns of viral loads in wastewaters. In Mexico, no systematic efforts have been reported in the use of this strategies. In this work, we quantified SARS-CoV-2 in rivers and irrigation canals in the Mezquital Valley, Hidalgo, an agricultural region where wastewater from Mexico City is distributed and used for irrigation. Using quantitative RT-PCR, we detected the virus in 6 out of 8 water samples from rivers, and 5 out of 8 water samples from irrigation canals. Notably, samples showed a general consistent trend of having the highest viral loads in the sites closer to Mexico City, indicating that this is the main source that contributes to detection. Using the data for SARS-CoV-2 concentration in the river samples, we generated a simplified transport model that describes the spatial patterns of dispersion of virus in the river. We suggest that this model can be extrapolated to other wastewater systems that require knowledge of spatial patterns of viral dispersion at a geographic scale. Our work highlights the need for improved practices and policies related to the use of wastewater for irrigation in Mexico and other countries.

The ongoing global pandemic of COVID-19 disease, caused by severe acute respiratory 41 syndrome coronavirus 2 (SARS-CoV-2), is a public health emergency of international 42 concern (Organization and Fund (UNICEF), 2020a, 2020b). SARS-CoV-2 ribonucleic acid 43 (RNA) has been detected in feces from both symptomatic and asymptomatic patients (Chen 44 et al., 2020; Holshue et al., 2020; Jiehao et al., 2020; Tang et al., 2020; W. Wang et al., 45 2020; Zhang et al., 2020) and in wastewater (Ahmed et al., 2020; Lodder and Husman, 46 wastewater has emerged as a cheap, efficient method for monitoring active cases in large 48 populations (Ahmed et al., 2020; S. Wang et al., 2020) , small towns (Kitajima et al., 2020; 49 Randazzo et al., 2020) , or campuses (Harris-Lovett et al., 2021) . Notably, this strategy 50 allows for a one-week anticipation in the active cases, compared to health systems 51 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted https://doi.org/10.1101 https://doi.org/10. /2021 registries, since asymptomatic individuals contribute to the viral load in wastewaters 52 (Vallejo et al., 2020; Wu et al., 2020) . 53

Mexico City has more than 661,446 confirmed cases of Government, 2020; consulted on June 1 st , 2021); this is the city with the highest number of 55 cases in the country. In Hidalgo, a state north of Mexican Valley Metropolitan Area 56 (MVMA, Figure 1a ), more than 39,012 positive cases have accumulated (State of Hidalgo 57 Government, 2021) , of which more than 11,000 cases (28%) correspond to the Mezquital 58

Valley, a highly productive agricultural region. 59

To date, few systematic efforts have been made in Mexico to detect SARS-CoV-2 in 60 wastewater. However, the Mezquital Valley has several relevant characteristics for the 61 study of SARS-CoV-2 in wastewater: 1) agriculture production is maintained by using 62 exclusively wastewater for irrigation (Contreras et al., 2017) ; 2) the wastewater source is 63 the MVMA, the most populated metropolitan area worldwide, and the region that 64 concentrates most active cases in Mexico (Figure 1b ) (Información referente a casos 65 COVID-19 en México -datos.gob.mx/busca) ; 3) the system includes one of the largest 66 wastewater treatment facilities in Latin America, which feeds a river and a complex system 67 of irrigation canals; 4) farmers, inhabitants and consumers in the Mezquital Valley are in 68 contact with water, soil or agricultural products and 5) the use of wastewater for irrigation 69 is one of the main causes that allowed that this Valley is no longer in extreme poverty 70 (García-Salazar and García-Salazar, 2019) . 71

Using data for SARS-CoV-2 concentration in wastewater, several models have been 72

proposed for to find a correlation between the temporal patterns of viral concentration and 73 the number of active COVID-19 cases (Hart and Halden, 2020b) . Likewise, a previous 74 work presented the first model of spatial and temporal patterns of viral loads in seaway 75 systems, showing the dispersion of the virus in an urban region (Hart and Halden, 2020a) . 76

However, models for spatial patterns of viral dispersion are needed in open waterbodies 77 that contain wastewater, in order to understand the virus transport and to identify the zones 78 with higher risk of infection. 79

In this study we sampled water from the Tula River, Salado River and irrigation canals in 80 the Mezquital Valley, which receive wastewater from Mexico City, to assess the presence 81 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted https://doi.org/10.1101 https://doi.org/10. /2021 of SARS-CoV-2 and generate a mathematical model that describes its spatial dispersion. 82

We propose that our results highly relevant not only to follow the epidemic in Mexico City 83 and municipalities in Hidalgo, but also to evaluate a possible risk of transmission through 84 environmental matrices and measure the stability of SARS-CoV-2 with geographic 85 resolution. 86

Sampling. Water samples were taken along the Tula River between the mouth of the 88 Central Interceptor Tunnel and Ixmiquilpan; samples were also taken in the Salado River, 89 which receives wastewater from the Grand Drainage Canal, and Tepeji river, which 90 contains wastewaters from local municipalities ( Figure 1 ). We also collected water samples 91 from irrigation canals in locations representative of the Mezquital Valley. Appropriate 92 safety equipment was always used, consisting of a cotton lab coat, latex gloves, KN95 93 respirator-mask, rubber boots, disposable cap, and safety glasses. A simple sampling 94 technique was used (NOM, 1980; EPA, 2017) , locating sites where the wastewater is well 95 mixed near to the center of the flow channel, approximately between 40 and 60 percent of 96 water depth, where turbulence is maximum, and there is minimum sedimentation of solids. 97

For each location, three water samples were collected as follows: two samples of 400 ml in 98 glass bottles, for SARS-CoV-2 detection and for microbiological analyses; and one 4 L 99 sample in a plastic bottle, for physicochemical analysis. For each water sample collected at 100 an irrigation canal, we sampled 500 g of soil from an adjacent agricultural field. All 101 samples were immediately placed in ice until arrival at the laboratory. in 150 ml of 10% beef extract buffer (pH 7) by stirring for 30 min (Horm et al., 2012) . 120

Next, soil suspension and inactivated wastewater samples (150 ml) were filtered through a 121

No. 5 Whatman filter (Millipore), and then through 0.22 µm polyethersulfone membrane 122 (Corning). Next, viral particles were precipitated by adding NaCl (100 g/L) and 123

Polyethilenglicol (22 g/L) and stirring for 20 min. Then, 105 ml samples were centrifuged 124 at 12,000 x g for 2 hours, and the resulting pellet was suspended in 400 µl RNAse free 125

water. Viral nucleic acids were extracted from these samples using the Purelink Viral 126 DNA/RNA kit (Invitrogen). Purified nucleic acid samples were quantified by 127 spectrophotometry in a Nanodrop One (Thermo Scientific). 128

Quantification of SARS-CoV-2 RNA. For detection of SARS-CoV-2, the kit Decov2 Triplex 129 (Genes2Life, Irapuato, Mexico) was used, which includes reverse transcription and PCR 130 detection of three targets of N ORF (N1-FAM, N2-HEX and N3-TexasRed) in a single 131 multiplex reaction. For each reaction, 5 µl of viral RNA were added as template in a total 132 volume of 25 µl. The RT-qPCR reaction was performed in a QuantStudio 5 (Thermo 133 Scientific) instrument, and settings for passive reference was changed to 'none'. Duplicate . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint dispersion of virus in unsaturated media (Torkzaban et al., 2006) was adapted. The original 143 model describes the viral concentration with respect to the distance from the virus input site 144 and the decrease over time, and considers terms of adsorption and detachment of virus with 145 respect to the soil-water interface and air-water interface. We considered only dispersion in 146 the water bulk; we also considered that dispersion of virus is independent on time, and it 147 depends on the distance. Hence, the attachment and detachment rate coefficients and the 148 inactivation rate coefficient in soil and air media were equal to zero (κ a att = 0, κ a det = 0, κ s att 149 = 0, κ s det = 0, μs = 0 and μa = 0). We also assume that Darcy flux (q) and inactivation rate 150 

. CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. Central Interceptor Tunnel, and Grand Drainage Canal (Fig. 1b) . Subsequently, the water is 178 collected in the Irrigation Districts (003-Tula, 100-Alfajayucan, and 112-Ajacuba), and a 179 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint dam system that includes Taxhimay, Requena, Endhó, Javier Rojo Gómez, and Vicente 180 Guerrero dams. This dam system is considered the largest in the world (Islas, 2010) . 181

Wastewater is partially processed in the wastewater treatment plant (WWTP) in Atotonilco 182 de Tula, Hidalgo (Fig. 1c) The WWTP normally works at 30% of its capacity because the producers refuse to use the 188 treated water in their irrigation systems. For this reason, this is a health and environmental 189 risk because these wastewaters irrigate more than 80,000 ha of crops (Lesser et al., 2018) . directly increase production costs, price of water, and increased needs for fertilizers, which 196 could impact land rentability (Pérez Camarillo, 2002; Pérez, Zacatenco and Martínez, 2006; 197 SIAP, 2018) . Table 1 ). Water samples were also collected from irrigation canals adjacent 204 to agricultural fields as well as soil samples from these agricultural fields (Fig. 1c, Table 1 ). 205

Produce samples were also collected at three of the agricultural fields: a sample of 206 coriander at site 3, and samples of lettuce at sites 6 and 7. In total, our sampling covered 207 ≈80 km in the Mezquital Valley, and included the municipalities of Tepeji del Río, 208

Atotonilco de Tula, Tula de Allende, Tezontepec de Aldama, Mixquiahuala de Juárez, 209 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. 

We detected RNA from SARS-CoV-2 in water samples collected in the Tula River, Tepeji 215 River and Salado Rover (Fig. 2) . Detection was achieved from the three targets included in 216 the kit (N1-FAM, N2-HEX and N3-TexasRed) in most cases; however, quantification using 217 N2-HEX Ct values and its corresponding standard curve yielded more consistent results, 218

and absolute values were always intermediate to those obtained with N1-FAM and N3-219 TexasRed (not shown). From these criteria, we use N2-HEX data throughout this study. 220 SARS-CoV-2 RNA was detected in 6 out of 8 water samples from river (Fig. 2) . As 221 expected, the highest concentration was found in sample RW2, at the entrance flow of the 222 wastewater treatment plant (WWTP, Fig. 1c and 2) , with a concentration of 79 RNA copies 223 per ml; from the sampled locations in the Tula River, this is the closest to the Mexican 224

Valley Metropolitan Area (MVMA, Fig. 1 and 2 ). This value decreased through the flow of 225 the river (which consists mostly of untreated wastewater) in samples RW3 and RW4, and 226 was undetectable in RW5, downstream of the Endhó Dam. SARS-CoV-2 was also detected 227 at the entrance fluxes of Tepeji River (RW1, 18 copies per ml) and Salado River (RW6, 24 228 copies per ml), both of which contribute to viral load in the Tula River. Finally, SARS-229

CoV-2 was not the detected in sample RW8, which was collected at Ixmiquilpan, ≈40 km 230 downstream of sample RW7 (Fig. 2) . 231 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. however, untreated wastewaters from municipalities in Hidalgo are also connected to these 241 canals. Since the irrigation canal network in the Mezquital Valley is highly complex and a 242 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint detailed map is unavailable, we only show the general known source of water in each 243 location (Fig. 3a) . RNA From SARS-CoV-2 was detected in 5 out of 8 water samples 244 collected from irrigation canals (Fig. 3b) . The highest concentration of 112 copies per ml 245 was found in sample CW1 (Fig. 3b) . This location is the closest from MVMA, however, it 246 is reportedly fed solely from wastewater treated in the WWTP (Fig. 3a, table 1 ). SARS-247

CoV-2 ARN was also detected in samples CW2, CW4, CW4-II and CW5, all of which are 248 fed from the WWTP, but also from wastewater from municipalities in Hidalgo, and from 249 the Endhó Dam (Fig. 3) . SARS-CoV-2 was not detected in samples CW3, CW6 and CW7; 250 notably, irrigation canals at Ixmiquilpan (CW6 and CW7) are fed from freshwater bodies 251

(not wastewater) such as groundwater wells or local spas, while CW3 is reportedly fed 252 from the WWTP and local municipalities (Fig. 3) . 253

Since SARS-CoV-2 RNA was detected in water samples from irrigation canals, we 254 hypothesized that it may be detectable in agricultural soil from adjacent fields (Fig. 1c , 255 Table 1 ). However, SARS-CoV-2 was not detected in these samples (Supplementary Table  256 S1 and S2). Similarly, SARS-CoV-2 RNA was not detected in any of the produce samples, 257 which were collected in the field or at the Ixmiquilpan Market (Table 1, Supplementary  258   Table S2 ). Since the internal control PMMV was detected in all of these samples 259 (Supplementary Table S2 ), we discard that the presence of PCR inhibitors as the reason for 260 lack of detection, but further studies are needed to confirm the absence of SARS-CoV-2 261 since viral particles can adsorb to soils and other solids. 262 263 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. (NOM-001-SEMARNAT-1996) . Regarding 274 limits for microbiological parameters (NOM-001-ECOL-1996) , 5 out of 8 water samples 275 from the Tula River, and 5 out of 8 water samples from irrigation canals, presented total 276 coliform values above the allowed limits for wastewater used for irrigation (Supplementary  277   Table S4 ). 278

We assessed if the physicochemical characteristics of wastewater, organic matter and 279 microbial concentration correlated with the concentration of the virus. In samples from the 280 river water, correlation analyses showed that several variables were associated with SARS-281

CoV-2 RNA concentration. In contrast, analyses using parameters obtained from irrigation 282 canals, showed no significant correlations between SARS-CoV-2 RNA concentration and 283 physicochemical or microbiological variables (Table 2, right). Significant p values were 284 obtained for correlation analyses with physicochemical parameters BOD, COD, pH, and SS 285 (Table 2 , left), and also for all three microbiological parameters in river samples (Table 2 , 286

Supplementary Figure S1 ). Further inspection of correlation trends revealed correlations 287 with pH and SS could be spurious, since they were highly grouped in discrete values 288 (Supplementary Figure S1) , and a higher number of samples should be analyzed to confirm 289 this observations (Table 1 , Suplementary Figure S1 ). 290 291 is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. Interestingly, the trend is the same than the virus concentration (Supplementary Figure S2) . 302 303

Using data for SARS-CoV-2 concentration in the Tula River, we sought to adapt a model 305 that describes viral dispersion in the wastewater bulk. Our model only considers the 306 dispersion of the virus in water and the modification of the flux in the mainstream. The 307 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint dispersion coefficient was calculated through least square optimization to the experimental 308 data (Suplementary File 1) (Molugaram et al., 2017) . The concentration in the initial 309 sampling site RW2 (Figure 1c .) was normalized to 1 (Ratio of Concentration C/initial 310 Concentration Ci); since it was the maximun value, the experimental data were normalized 311 to this value. Additionally, we modeled two entrances at the points RW2 and RW6, as a 312 result the dispersion coefficient increases at these points. The model fitted to the 313 experimental data along the Tula River (Figure 4a ). Therefore, with only three variables, 314 dispersion coefficient (D), amount of water (Θ) and a distance function of D [D(x)], we 315 could define the dispersion of the virus in the Tula River. Finally, we used QGIS3 to obtain 316 a geographic representation of our model and the experimental data (Figure 4b) , which 317

show the general trends of SARS-CoV-2 dispersion in the Tula River. 318 319 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted https://doi.org/10.1101 https://doi.org/10. /2021 CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted https://doi.org/10.1101 https://doi.org/10. /2021 In this work, we quantified SARS-CoV-2 ARN in wastewaters from Mexico City, which 328 are distributed throughout the Tula River, Salado River and irrigation canals and are used 329 for irrigation of crops in the Mezquital Valley. Notably, we detected the virus in 330 geographically representative water samples from both rivers and the irrigation canals. 331

With our data, we generated a viral dispersion model which can be used to assess Our results showed that the SARS-CoV-2 virus was not detected on soil samples. While 344 this could be related to PCR inhibitors in the samples, we found that the PMMV virus was 345 detected and hence discarded this hypothesis. Virus associate with soil and other particulate 346 matter and both adsorption and detachment of virus depends on temperature, moisture, pH, 347 and the physicochemical characteristics of the virus capsid surface and the particles. 348

Similarly, the microbes and organic matter may have a protective effect on virus 349 (AzadpourKeeley, Faulkner and Chen, 2003) . Further studies are needed to asses if lack of 350 detection of SARS-CoV-2 is related to degradation or dispersion of the virus, or 351 alternatively, if viral particles adsorb in the soil matrix, which would make our ARN 352 extraction method not appropriate. 353

We found that physicochemical variables COD and BOD and microbiological variables 354 showed significant correlations with SARS-CoV-2 quantification, but only in samples from 355 the Tula River. However, these observations should be confirmed with measurements in a 356 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint higher number of samples. This result suggests that in the river, anthropological sources 357 from a single source of contamination predominate, i.e. the MVMA. However, in irrigation 358 canals -where no correlations were found -may receive other sources of contamination 359 (from agriculture, livestock, or industry) (Guédron et al., 2014; Lesser et al., 2018) . 360

Furthermore, our correlation analyses suggest that BOD, COD, and the Biodegradability 361

Indec (BOD/COD), as well as fecal coliforms may be good indicators of SARS-CoV-2 362 ARN concentration in municipal wastewaters. 363

The model proposed to explain the dispersion of SARS-CoV-2 virus along the Tula River, 364 as well as the experimental data, indicate that the viral concentration decreases from south 365 to north, with an initial dispersion point at the entrance of the Tula River at the WWTP and 366 a minimal contribution from the communities along the Mezquital Valley. Our model 367 predicts viral dispersion in the Mezquital Valley, and may be useful for selection sampling 368 locations prior to temporal monitoring to quantify the evolution of SARS-CoV-2 (or other 369 virus) epidemics in populations. Previously available models for viral dispersion in 370 environmental matrices (Bivins et al., 2020; Farkas et al., 2020; Kitajima et al., 2020) are 371 useful for detailed dissection of variables governing dispersion patterns of viral particles in 372 at a smaller scale in controlled environments. Our model is, to our knowledge, the first to 373 allow prediction of viral dispersion in linear water bodies at a geographic scale. This model 374 could be extrapolated to other rivers, streams, and canals. 375

One of the main purposes of this work was to assess the possible risk of environmental 376 transmission of SARS-CoV-2 through environmental matrices. Indeed, some recent reports 377 suggest/show that the virus may be infective (Kitajima et al., 2020) , and hence, direct 378 contact with water bodies in the Mezquital Valley may represent a risk of transmission, 379 especially for farmers during flooding irrigation (Lüneberg et al., 2018) . However, this 380 work does not seek to eliminate wastewater usage in the Mezquital Valley, as this practice 381 is one of the key factors that allowed the economic development of the region. In fact, the 382

Mezquital Valley is considered a study model for the agricultural development of arid and 383 semi-arid rural regions (Anderson, 2020; Bonvehi Rosich and Seth Denizen, 2021; Seth 384 Denizen, 2021) . We suggest that our work should be considered for the creation and 385 modification of practices and policies related to water treatment (Belhadi et al., 2020) , 386 . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Available at: https://www.gsd.harvard.edu/2020/09/the-right-to-sewage-agricultureclimate-change-and-the-growing-need-for-cities-to-embrace-wastewater-reuse/ (Accessed: . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

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The copyright holder for this preprint this version posted June 12, 2021. . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 12, 2021. . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)The copyright holder for this preprint this version posted June 12, 2021. ; https://doi.org/10.1101/2021.06.07.21258522 doi: medRxiv preprint