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Prevalence of Human Sapovirus in Low and Middle Income Countries

Prevalence of Human Sapovirus in Low and Middle Income Countries Hindawi Advances in Virology Volume 2018, Article ID 5986549, 12 pages https://doi.org/10.1155/2018/5986549 Review Article Prevalence of Human Sapovirus in Low and Middle Income Countries 1 1 Mpho Magwalivha , Jean-Pierre Kabue, 1 1,2 Afsatou Ndama Traore, and Natasha Potgieter Department of Microbiology, School of Mathematical and Natural Sciences, University of Venda, South Africa Dean of School of Mathematical and Natural Sciences, University of Venda, South Africa Correspondence should be addressed to Mpho Magwalivha; mpho.magwalivha@univen.ac.za Received 30 May 2018; Accepted 25 July 2018; Published 2 September 2018 Academic Editor: Jay C. Brown Copyright © 2018 Mpho Magwalivha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Sapovirus (SV) infection is a public health concern which plays an important role in the burden of diarrhoeal diseases, causing acute gastroenteritis in people of all ages in both outbreaks and sporadic cases worldwide. Objective/Study Design.The purpose of this report is to summarise the available data on the detection of human SV in low and middle income countries. A systematic search on PubMed and ScienceDirect database for SV studies published between 2004 and 2017 in low and middle income countries was done. Studies of SV in stool and water samples were part of the inclusion criteria. Results.From19low and middle income countries, 45 published studies were identified. The prevalence rate for SV was 6.5%. A significant difference ( P=0) in SV prevalent rate was observed between low income and middle income countries. Thirty-three (78.6%) of the studies reported on children and 8 (19%) studies reported on all age groups with diarrhoea. eTh majority (66.7%) of studies reported on hospitalised patients with acute gastroenteritis. Sapovirus GI was shown as the dominant genogroup, followed by SV-GII. Conclusion.The detection of human SV in low and middle income countries is evident; however the reports on its prevalence are limited. There is therefore a need for systematic surveillance of the circulation of SV, and their role in diarrhoeal disease and outbreaks, especially in low and middle income countries. 1. Introduction disposal, poor water quality, poor health status, and disease transmission through faecal-oral route [6]. An estimated number of 6.3 million deaths of children under Amongst diarrhoeal causing agents, Sapovirus (SV) the age of 5 years suffering from diarrhoea have been reported is one of the enteric viruses that cause acute gastroen- worldwide [1, 2]. In Africa, death due to diarrhoeal disease teritis in humans and animals. Sapoviruses were previ- remains a major health concern, though it has decreased ously called “typical human Caliciviruses” or “Sapporo-like from 2.6 million to 1.3 million between 1990 and 2013 [3]. viruses” in the family Caliciviridae [7]. They are identified Diarrhoeal disease is the important cause of morbidity and as nonenveloped, positive-sense, single-stranded ribonucleic mortalityinlow andmiddleincomecountries,alsothe acid (RNA) genome of approximately 7.1 to 7.7 kb in size third most frequent cause of death and greatest contributor with a poly(A) tail at the 3’-end [8–10]. Amongst the vfi e to the burden of disease in children younger than 5 years designated genogroups (GI to GV), GIII infects porcine of age [4]. eTh infection of human intestinal tract occurs species [11–14], while GI, GII, GIV, and GV infect humans through transmission at the household level due to different [15]. Currently, human SV genogroups are classified into pathways such as ingestion of contaminated food and water, 16 genotypes (comprising seven genotypes for GI and GII, poor waste disposal, and person-to-person interactions in the respectively,andonegenotypeeachforGIVandGV)through households and community [4, 5]. Low and middle income phylogenetic analysis of the complete capsid gene [15, 16]. countries still face challenges like inadequate human waste Coinfections of SVs with other enteric viruses (such as 2 Advances in Virology noroviruses [NoVs], rotaviruses [RVs], astroviruses [AstVs], Studies identified for possible inclusion adenoviruses [AdVs], enteroviruses [EVs], and kobuviruses (n=138) [KbVs]) have been noted in acute gastroenteritis outbreaks in humans [17–19]. Excluded based on country’s status (n= 93) This review summarises reports on SV detection and typing in low and middle income countries. In addition, it highlights the need to establish the relatedness of circulating SV strains in environmental (water) samples and clinical Studies which met the inclusion criteria (n=45) samples from communities in low and middle income coun- tries (particularly rural settings). eTh time-frame chosen was 2004 to 2017 because of the availability of published data on human SV within the low and middle income countries. Studies on stool samples (n= 41) 2. Methodology Study on stool & environmental sample (n=1) Two literature searches were carried out. The first literature Studies on environmental sample (n=3) search was performed using the terms: calicivirus, sapovirus, and developing countries, as listed by National Institutes of SV positive studies, which did Health PUBMED library and ScienceDirect. A second litera- not identify genogroups (n=11) ture search was independently done for each of the 139 “devel- oping” countries accessed from the list published by the Soci- ety for the Study of Reproduction (http://www.ssr.org). Fur- Studies which identified SV genogroups (n=33) thermore, the identified countries were then assessed accord- ingtothe 2018WorldBankanalyticalclassicfi ation report Figure 1: Schematic diagram showing search process for selection (http://datahelpdesk.worldbank.org/knowledgebase/articles/ of studies reported. 906519). For a successful search, each of the countries' names was combined with the following keywords: cali- civirus, sapovirus, enteric viruses, and gastroenteritis. Studies selection based on the selection criteria (Figure 1), a total of identified by the search terms were selected for inclusion in 45 studies met the inclusion criteria. From 45 publications, the review based on the following inclusion criteria: 41 reported on clinical (stool) samples, 3 on environmental (a) Studies limited to human SV detected in clinical (water) samples, and 1 on both. Of the 42 studies conducted specimen and environmental water samples, reported on clinical specimens, 66.7% (n=28) were done in hospi- in the 21st century. talised patients, 23.8% (n=10) in outpatients, and 9.5% (n=4) (b) SV studies using laboratory molecular techniques in both hospitalised and outpatient settings. including nested-PCR (nPCR), real time-PCR (RT- PCR), and RT-multiplex PCR. 3.1. SV AgeDistributioninHuman Populations. The majority of studies (78.6%; 33/42) investigated SV in children less than Studies were excluded from the review if SV was detected 5 years of age and a further 19% (8/42) included all ages. in other mammalian species or animals or if the study was However, only a single study investigated SV in adults with conducted in high income countries. In case of duplication diarrhoea or acute gastroenteritis. of studies by authors, only one article was included. Data was extracted from each selected study when 3.2. Seasonality. eTh detection of SV from clinical samples provided: country name and its economic status (i.e., low based on seasonality was reported in only 14.3% (6/42) of income, lower, and upper middle income) as per the analyti- the studies. eTh majority (42.9%, 18/42) of the studies did cal classification report by World Bank, study setting (hospi- not report on the time-frame of detection, 38% (16/42) of talised, outpatient, and environment), study population (age the studies showed inconsistent time-frame of detection, and group), population size, duration of the study, diagnostic 4.8% (2/42) of the studies showed detection throughout the method used, number of samples tested for SV (including year. Studies investigating SV in water sources in South Africa their genogroups and genotypes), rfi st author, and year of (SA) did not detect any seasonal peaks. publication (Tables 1, 2 and 3). Five studies reported on samples collected within a period The difference of SV data in middle and low income of 2 to 4 months, and these cases were not defined as countries was analysed for statistical significance by Student’s outbreaks, while the duration period of sample collection for t-test using the simple interactive statistical analysis (SISA) at other 40 studies ranged over periods from 1 year to 5 years. http:home.clara.net/sisa. Result with P< 0.05 was considered significant. 3.3. Sapovirus Detection and Genotyping. From the 42 included studies, 41 of these reported SV positive cases while 3. Results only one study on adults reported negative results (Tables A total of 138 articles published from 2004 to 2017 were 1 and 2). Mixed infection of SV with bacteria and/or other identified from 19 low and middle income countries. Aer ft enteric viruses was identified in 19.5% (8/41) of the studies, a Advances in Virology 3 fi fi fi Table 1: Summary of human SV detection from 33 studies (stool samples) conducted in 14 non-African low and middle income countries. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Study setting Genotypes of year  population size study incidence) 2.7 % SV Lower middle Infants/ From 2004 to Oct 2004 – Jan 2005, Bangladesh 917 HP with AGE RT-PCR (All in<3yrs of age) Dey et al [20] income Children 2005 Sept 2005 SV-GI.1, GI.2 15/305 (4.9%), mixed From March March, May - infection of SV and Astv in Children 305 HP severe GE to September RT-PCR Aragao et al [21] September 1sample SV-GII.1, SV-GI.1, SV-GI.2 OP (81 = diar; From April Children (0 – 2 of 81: 2.5% SV (GI.1, 159 78 = 2008 to July February, April RT-PCR Aragao et al [22] 10 yrs GII.2) non-diar) 2010 From October Children Day Care RT- multiplex 25/539 (4.6%) SV, de Oliveira et al [23] 539 2009 to Not dened Upper middle (6-55 mn old) (Healthy) PCR SV-GI.1, GI.3 Brazil October 2011 income 12/341 (3.5%) [/–HP, HP Quantitative Children, 212 From 2012 to / – OP]. OP Not dened real-time Fiorettietal[24] outpatients 129 2014 SV-GI.1 dominant, GI.2, With AGE PCR (qPCR) GI.6, GII.1, GV.1 426 From January Children 6/156 (3.8%), (156 of<3yrs HP with AGE 2010 to Aug & Sept RT-PCR Reymao et al [25] < 10yrs SV-GI.1, GI.2, GII.2, GII.4 tested) October 2011 From 1990 t0 9/172 (5.2%) Children 172 Community Not defined Nested PCR Costa et al [26] 1992 SV-GI.1, GI.7, GII.1, GV.2 9/477: 1.89% SV (<24 OP with acute month children), mixed From August Children (477)/ infection of SV & AdV in 1 500 to November Aug–Nov2010 RT-PCR Ren et al [27] <5yrs old persistent (23) sample, diar SV-GI dominant, SV-GII & SV-GIV Upper Middle China [9/412] 2.2% SV single income infection, Co-infection: From August 2/412 ETEC with SV, 1/412 Patients (1mn HP & OP with 2014 to Salmonella sp with SV, 412 Not dened RT-PCR Shen et al [28] –78yrs) AGE September 1/412 Salmonella sp with SV &AdV Genogroups not defined 4 Advances in Virology fi fi Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Method used Reference Classification as Study Population Duration of or defined period of Study setting Genotypes of year  population size study incidence) From August 23/226 (39%), mixed Multiplex India (New Lower middle Children 2000 to infection in 5 samples Rachakonda et al 226 HP with AGE Not dened two-step Delhi) income <10yrs December {NV-GII and SV-GI} [29] RT-PCR 2001 SV-GI[22],GII[1] From 2008 to 6/200 (3%), Parsa-Nahad et al Children 200 HP with AGE Winter and in fall RT-PCR 2009 SV-GII [30] Upper middle Patients (3 mn Iran 11.9% SV (patients with income -69yrs;mean From May to 42 HP with AGE May – July 2009 RT-PCR <5yrs of age) Romani et al [31] 15.3yrs July 2009 SV-GI.2 Lower middle From July to 1/36 (2.8%) pos for SV Hansman et al Mongolia Infants 36 households Jul–Aug 2003 RT-PCR income August 2003 SV-GI [11, 12] 57/330 (17%): HP =  % From (175 HP; 155 Nov 2009- Feb/Mar [ ], OP = % Lower middle Children September Real-time Nicaragua 330 OP), with 2010, May-Aug/Sept [/ ]. Bucardoetal[32] income <5yrs 2009 to PCR AGE /diar 2010 SV-GI, GII, GIV{HP: GI.1, October 2010 GI.2; OP: GII.2, GII.3 13.9% SV detection (12.3% 122 Pos: Infants From 1990 to SV mono-infections, 1.6 Enteric HP with AGE Mar, Aug - Oct RT-PCR Phan et al [33] <6to>35 mn 1994 mixed infection – AstV & Viruses SV), SV-GI Lower middle Pakistan 1990: Aug, Sept, Oct income Infants & 1991:Jan,May,Jul, 3.2 % SV children<1 From 1990 to Oct RT-PCR 517 HP with AGE SV-GI dominated, followed Phan et al [34] mn – 5yrs 1994 1992:Mar,Aug,Sep by GII, and GIV 1993: Sep 1994: Apr, July From August Papua New 4/199 (2%) SV, Lower middle Children 2009 to Guinea 199 HP with AGE Not dened RT-PCR Soli et al [35] Genogroups not defined income <5yrs November (Goroka) 2010 Advances in Virology 5 fi fi fi Th Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Genotypes Study setting of year  population size study incidence) 9.0% overall: Quantitative ∗. % [ /] reverse diarrhoeal – SV-GI/1/2/6/7, Upper middle Children 300 non-diar, From 2007 to Peru 599 Four seasons transcription- GII.1/2/4/5, GIV, GV/1; Liu et al [36] income <2yrs 299 diar 2010 real-time ∗ . % [ /] PCR (qPCR) non-diarrhoeal – SV-GII.5, GIV 29/417 (7%) detection, (co-infection in 10/29: 6/10 From June Lower middle Children Real-time with RV, 2/10 with NV, 2/10 Philippines 417 HP with AGE 2012 to Not dened Liu et al [1, 2] income <5yrs PCR with AstV). August 2013 SV-GI.1, GI.2, GII.1, GII.4 &GV From 15%: 11% single infection, 80 randomly November 4% mixed infection – NoV Infants HP with AGE Nov2002–April2003 RT-PCR Guntapong et al [37] selected 2002 to April &SV), 2003 SV-GI 3/248 (1.2%) SV- single Children From 2002 to 248 HP with AGE Not dened RT-PCR infections Khamrin et al [38] <5yrs 2004 SV-GI [GI.1 &GI.2], GIV 25%, mixed infection I 1 From May Jun-Jul, Jan-Mar, sample (NV-GI and SV) Children 296 HP with AGE 2000 to RT-PCR Malasao et al [39] May-Jul, Mar. SV-GI.1, GI.4, GI.5, GII.1, March 2002 GII.2 From January HP with Early summer: March 0.8% SV All age groups 273 2006 to RT-PCR Kittigul et al [40] Upper middle AGE/diar &April SV-GII/3 Thailand February 2007 income Children January to 5/147 (3.4%) SV HP with (Neonate to 147 December Not dened RT-PCR SV-GI [GI.2, GI.1, GI.5] Khamrin et al [41] AGE/watery 5yrs old) 2005 dominating, SV-GII.3 January to Pediatric RT-multiplex 5/160 (3.1%) SV Chaimongkol et al 160 HP with AGE December roughout the year Genogroup not defined patients PCR [42] In 2007, and Children 2007:Feb,Sept,Oct. Semi-nested 7/567 (1.2%), Chaimongkol et al 567 HP with AGE from 2010 to <5yrs &2010: Dec RT-PCR SV-GI.1 [43] Adult (15yrs – RT- multiplex 332 HP with diar Year 2008 Not defined No SV detected Saikruang et al [44] 90yrs) PCR 1.1% SV, mixed infection of NoV-GII & SV in 2 From 2006 to Pongsuwanna et al Patients 1141 HP with AGE May - July RT-PCR samples 2008 [45] Genogroup not defined 6 Advances in Virology fi Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Genotypes Study setting of year  population size study incidence) From HP with acute December 1/448 (0.2%) SV Children 448 sporadic 1999 to Not dened RT-PCR Hansman et al [46] SV-GI gastroenteritis November 0.8% SV (0.4% From October monoinfection, 0.4% Paediatric HP with viral 2002 to Oct 2002 – Sep 2003, 1010 RT-PCR Nguyen et al [47] coinfection), patients AGE September Rainy season (July) Genogroup not defined From Lower middle Vietnam income December Pediatric 502 HP with AGE 2005 to Dry season RT-PCR 1.2% SV Nguyen et al [48] November 1.4% SV From SV-GI and SV-GII Children November Cooler months (Oct – Real-time 501 HP with AGE Co-infection of (NoV & Trang et al [49] <5yrs 2007 to Feb) RT-PCR SV) in 1 sample, of (NoV, October 2008 SV, and RV) in 1 sample Independent See information From January States of the Real-time 16/495 (3.2%) below describing Children 495 HP with AGE to December Jan - Mar, May – Aug Chhabra et al [50] former Soviet PCR SV-GI.1 dominating the States 2009 Union HP = hospitalised patient; OP = outpatient; AGE = acute gastroenteritis; mn= month; yr(s) = year(s); diar = diarrhoea; SV = Sapovirus; G (I-IV) = genogroup (I-IV) ∗Independent States of the former Soviet Union refers to Armenia, Azerbaijan & Belarus (uppermiddleincomestatus), and Georgia, Republic of Moldova & Ukraine (lower middle income status). Advances in Virology 7 fi fi fi fi fi fi Table 2: Summary of human SV detection from 9 studies (stool samples) conducted in 5 African countries. World Bank Study setup Prevalence (seasons or Method Country Classification defined period of Rate of Detected Genotypes Reference Study Duration of used Population size Study setting as of year  population study incidence) 9%: 27/263 (10.3%){5/27 = 263 diarrhoeal, From November hospitalised, 22/27 = Urban area (HP Real-time Ouedraogo Children 50 2011 to Not dened non-hospitalised}& 3/50 (6%) &OP) RT-PCR et al [51] non-diarrhoeal September 2012 SV-GII [GII.2, GII.1, GII.3], SV-GI.2 Burkina 56/309 (18%) [mixed infection: Low income Faso with RV 25/56, with NV 5/56; From May 2009 Real-time single infection 20/56] Matussek Children<5yrs 309 diarrhoeal Not defined Not dened to March 2010 PCR Genogrouping{34/56}:SV-GI et al [16] [GI.1, GI.4], GII [GII.1, GII.4, GII.6], GIV.1 & GV.1 Government 213 diarrheic From June to 9/213 (4.2%) Sisay et al Ethiopia Lowincome All agegroups Health Care June-sept 2013 RT-PCR samples September 2013 One sequenced (SV-GII.1) [52] Centre 5%: 13/334 (4%) and 31/524 (6%) Lower middle 334-Lwak & From June 2007 Shioda et al Kenya All age groups Clinics with diar Not dened RT-PCR SV income 524-Kibera. to October 2008 [3] Genogroups not defined 10/245 (4.1%) incl. one HP Not defined Real-time Mans et al Paediatric<13yrs 245 Year 2008 Mixed infection with NV gastroenteritis RT-PCR [53] Genogroups not defined 16/190 (8.4%): (1 - 62yrs: mean From July 2007 Patients 1mn to 94 diar Bio-wipes from Real-time Mans et al 24yrs) to December Not dened 87yrs mean 14yrs 93 non-diar rural households RT-PCR [54] Genogroups not defined 3unknown South Upper middle 221 were characterised Selected) 296 of Africa income From April 2009 (genotyped) 477 SV-Pos HP with Nested Murray et Children to December Not dened SV-GI [GI.1 – GI.3, GI.5, GI.6, (for gastroenteritis PCR al [55] 2013 GI.7], SV-GII [GII.1 – GII.7], characterisation) SV-GIV 238/3103 (7.7%) SV From 2009 to Higher in Summer & Real-time Page et al Children<5yrs 3103 HP diar Genogroups not defined 2013 Autumn (Nov to Apr) PCR [56] 6/788 (0.8%) [Mixed infection: 788 From January RT-PCR Sdiri- Lower middle Consulting for with RV 2/6; single infection Tunisia Children [408 HP, 380 2003 to April Not dened Primer Loulizi et al income AGE 4/6]. Positive from OP samples OP] 2007 Noel, 1997 [57] SV-GI.1 HP = hospitalised patient; OP = outpatient; AGE = acute gastroenteritis; mn= month; yr(s) = year(s); diar = diarrhoea; SV = Sapovirus; G (I-IV) = genogroup (I-IV). 8 Advances in Virology Table 3: Summary of human SV detection from 4 studies (water samples) conducted in low and middle income countries. World Bank Classification as Samples Prevalence Rate of Country Method used Reference of year  (season) detection Type Size Duration Quantitative From 2012 Summer and Fioretti et al Brazil Upper middle income Wastewater 156 real-time 51/156 (33%) to 2014 Autumn [24] PCR (qPCR) May, Aug, From 2009 Nov (2009); 48/99 Murray et al River water 99 RT-PCR to 2010 Jan, April (48.5%) [58] (2010) From August August South Real-Time Murray et al Upper middle income Wastewater 51 2010 to (2010), June, 37/51 (72.5%) Africa qPCR [59] December July (2011) Water January January and Real-Time Murray and (various 10 and March 8/10 (80%) March 2012 PCR Taylor [60] source) 2012 SV single strain was identified in 36.6% (15/41) of the studies, 4. Discussion and mixed strains of SV were identified in 43.9% (18/41) of This review provides a summary of studies conducted in the studies. From the 41 studies, only 31 studies reported SV developing countries on the detection of human SV. Only detection with identification of the genogroups/genotypes. 45 (41 stool samples, 3 water samples, and 1 both stool Overall detection of SV strains showed SV-GI.1 and GI.2 and water sample) studies satisfied the inclusion criteria as the most dominant[90%(28/31)] strain from different of this review highlighting the importance for systematic settings of studies, followed by SV-GII.1, GII.2, GII.3, and surveillance monitoring human SV circulating in developing GII.4 with the least detection of SV-GIV strain and –GV countries (rural and urban communities). Very little is known (GV.2) strain. No study showed the occurrence of SV- about the contribution of human SV to diarrhoeal disease in GIV as a single detection but only in mixed infection developing countries; this is reflected in the fact that reported cases. studies were only from 19 identified countries which include The prevalence rate of SV from the 41 documented 5 African countries, namely, Burkina Faso, Ethiopia, Kenya, studies in low and middle countries was 6.19% with a range South Africa, and Tunisia (Table 2). A total of 78.6% (33/42) from 0.2% to 39%. Further breakdown showed significant studies reported on children≤5yearsofagefromthe col- difference ( P =0)inSVprevalenceratebetween lowincome lected data, highlighting the role of SV in diarrhoeal disease (10.40%) and middle income (5.86%) countries. Although amongst children in the developing countries. Hence, SV and data on the prevalence of SV in African countries is limited, other emerging enteric viruses, being underappreciated, can thus far, eight studies have been conducted in urban settings. be an important cause of Norovirus negative outbreaks as Detection of SV from children in Africa is recorded with different incidence rates: in Tunisia [0.8%] [57], Burkina reported by Lee and colleagues [61]. In addition, since it is dicffi ulttoculture humanSVoncelllines[13], specialised Faso [18%,10.3%,respectively][16, 51], andSouth Africa [4.1%, 7.7%, respectively] [53, 56]. The prevalence of SV in molecular laboratories are needed for the investigation of all ages was reported from South Africa [8.4%] [54], Ethiopia such virus in the developing countries. Because of lack [4.2%] [52], and Kenya [4%] [3]. A predominance of SV-GIV of funding and skills, the prevalence of enteric viruses is (53/221, 24%) was noted in the South African study done on underreported in Africa and other developing countries [62] stool samples from hospitalised children with gastroenteritis Most of the studies (66.7%; 28/42) were done in hospi- [55]. talised patients, and this might be due to the fact that SV Only 8.9% of studies reported SV in the environmental infection sometimes leads to hospitalisation as illustrated and waste water samples from low and middle income from other studies [49, 63]. GEMS study reported SV countries. The detection of SV-GI, SV-GII, and SV-GIV has amongst other enteric pathogens to have been associated with been reported from polluted water sources by wastewaters moderate to severe diarrhoea in developing countries [64]. and also on samples collected from treatment plants within The Millennium Development Goals (MDG) 2015 report selected areas of SA [58–60]. Sapovirus genogroups I and II shows disadvantaged settings being vulnerable as compared were identified from river water samples, with detection rate with the advantaged or developed settings, highlighting the of 48.5% (48/99) [58], while, in Brazil, SV-GI (genotypes 1 eeff ctiveness and affordability of treatments, and improved and 2) were detected (33%, 51/156) from the wastewaters [22], service delivery and political commitment playing a role in Table 3. such settings. eTh statistical analysis of this review similarly Advances in Virology 9 showed a significant difference in the prevalence of SV in low public health intervention strategies. Furthermore, detection income than in middle income countries (P=0). of enteric viruses (such as SV) in environmental samples eTh circulation of SV genogroups shows variability, with gives awareness of the circulation of infectious viral particles SV-GI and SV-GII detected frequently, while SV-GIV and within the population and health-hazards which might be SV-GV are rarely detected comparing to other genogroups associated with the environment. eTh predictable eect ff s [16]. An African study (Burkina Faso) reported SV-GII as the of human waste disposal, water quality, and high rate of predominated strain, mostly in outpatients with diarrhoea immunocompromised society have been a big concern in (81.5%: 22/27), suggesting that this genogroup may be less low and middle income countries, but there are still few virulent and require fewer hospital admissions. However, documented reports on the detection of SV from environ- additional studies on outpatients will have to be conducted mental samples. This is highlighted by the finding of this to conrm fi this observation. Although the detection of SV- study with high prevalence of SV in low income countries. GII is seen in diarrhoeal samples, it might be less virulent to The survival and development of children depend on good cause severe symptoms leading to hospitalisation of patients, hygiene practices and use of clean drinking and domestic unlike SV-GI which is commonly known to be associated water on daily basis [4]. Monitoring of genetic diversity of with severe symptoms and frequently detected in patients the current circulating or emerging SV genogroups, possible presenting with gastroenteritis [16, 32]. eTh detection of SV water-borne transmission, and possible zoonotic infections (GI, GII, GIV, and GV) in gastroenteritis outbreak cases has amongst the communities is critical, and studies which can been reported in high income countries, however with less show the transmission of SV between the environment(s) detection rate of SV-GII in both cases [14, 17, 61, 65]. (especially river water), domestic animals, and human should Human SV infections cases relating to acute gastroenteri- be considered, and the role that SV plays in diarrhoeal tis in people of all ages have been identified worldwide [14]. diseases [69]. Notwithstanding the potential selection biases present based on the studies available for inclusion, this review shows that 5. Conclusion the prevalence in children may be higher than in adults in low and middle income countries. In addition, the GEMS study in This review found substantial evidence of SV proportion associated with diarrhoeal disease in low and middle income low and middle income countries highlights diarrheal disease countries. However there is limited data reporting the detec- in children as a leading cause of illness and death and also increasing the risk of delayed physical and intellectual devel- tion of circulating SV strains. eTh refore systematic surveil- lance of SV circulation within the communities in low and opment [66]. It has been reported that sporadic and outbreak cases caused by enteric viruses spread mainly by person- middle income countries is needed to assess sufficiently its to-person contact, contaminated surfaces or objects, and role in diarrhoea disease. contaminated water or food [67]. eTh refore children are more vulnerable than adults within such exposed environment, Conflicts of Interest probably because of immune system development. However, eTh authors declare that there are no conflicts of interest previous studies noted that gastroenteritis symptoms are regarding the publication of this paper. usually self-limiting, and patients usually recover within a couple of days depending on the individual immune’s response [49, 63]. Adults are likely to consider self-treatment References by oral rehydration solution (ORS) which is the safe, effective, [1] L. Liu, S. Oza, D. 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Prevalence of Human Sapovirus in Low and Middle Income Countries

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Hindawi Advances in Virology Volume 2018, Article ID 5986549, 12 pages https://doi.org/10.1155/2018/5986549 Review Article Prevalence of Human Sapovirus in Low and Middle Income Countries 1 1 Mpho Magwalivha , Jean-Pierre Kabue, 1 1,2 Afsatou Ndama Traore, and Natasha Potgieter Department of Microbiology, School of Mathematical and Natural Sciences, University of Venda, South Africa Dean of School of Mathematical and Natural Sciences, University of Venda, South Africa Correspondence should be addressed to Mpho Magwalivha; mpho.magwalivha@univen.ac.za Received 30 May 2018; Accepted 25 July 2018; Published 2 September 2018 Academic Editor: Jay C. Brown Copyright © 2018 Mpho Magwalivha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Sapovirus (SV) infection is a public health concern which plays an important role in the burden of diarrhoeal diseases, causing acute gastroenteritis in people of all ages in both outbreaks and sporadic cases worldwide. Objective/Study Design.The purpose of this report is to summarise the available data on the detection of human SV in low and middle income countries. A systematic search on PubMed and ScienceDirect database for SV studies published between 2004 and 2017 in low and middle income countries was done. Studies of SV in stool and water samples were part of the inclusion criteria. Results.From19low and middle income countries, 45 published studies were identified. The prevalence rate for SV was 6.5%. A significant difference ( P=0) in SV prevalent rate was observed between low income and middle income countries. Thirty-three (78.6%) of the studies reported on children and 8 (19%) studies reported on all age groups with diarrhoea. eTh majority (66.7%) of studies reported on hospitalised patients with acute gastroenteritis. Sapovirus GI was shown as the dominant genogroup, followed by SV-GII. Conclusion.The detection of human SV in low and middle income countries is evident; however the reports on its prevalence are limited. There is therefore a need for systematic surveillance of the circulation of SV, and their role in diarrhoeal disease and outbreaks, especially in low and middle income countries. 1. Introduction disposal, poor water quality, poor health status, and disease transmission through faecal-oral route [6]. An estimated number of 6.3 million deaths of children under Amongst diarrhoeal causing agents, Sapovirus (SV) the age of 5 years suffering from diarrhoea have been reported is one of the enteric viruses that cause acute gastroen- worldwide [1, 2]. In Africa, death due to diarrhoeal disease teritis in humans and animals. Sapoviruses were previ- remains a major health concern, though it has decreased ously called “typical human Caliciviruses” or “Sapporo-like from 2.6 million to 1.3 million between 1990 and 2013 [3]. viruses” in the family Caliciviridae [7]. They are identified Diarrhoeal disease is the important cause of morbidity and as nonenveloped, positive-sense, single-stranded ribonucleic mortalityinlow andmiddleincomecountries,alsothe acid (RNA) genome of approximately 7.1 to 7.7 kb in size third most frequent cause of death and greatest contributor with a poly(A) tail at the 3’-end [8–10]. Amongst the vfi e to the burden of disease in children younger than 5 years designated genogroups (GI to GV), GIII infects porcine of age [4]. eTh infection of human intestinal tract occurs species [11–14], while GI, GII, GIV, and GV infect humans through transmission at the household level due to different [15]. Currently, human SV genogroups are classified into pathways such as ingestion of contaminated food and water, 16 genotypes (comprising seven genotypes for GI and GII, poor waste disposal, and person-to-person interactions in the respectively,andonegenotypeeachforGIVandGV)through households and community [4, 5]. Low and middle income phylogenetic analysis of the complete capsid gene [15, 16]. countries still face challenges like inadequate human waste Coinfections of SVs with other enteric viruses (such as 2 Advances in Virology noroviruses [NoVs], rotaviruses [RVs], astroviruses [AstVs], Studies identified for possible inclusion adenoviruses [AdVs], enteroviruses [EVs], and kobuviruses (n=138) [KbVs]) have been noted in acute gastroenteritis outbreaks in humans [17–19]. Excluded based on country’s status (n= 93) This review summarises reports on SV detection and typing in low and middle income countries. In addition, it highlights the need to establish the relatedness of circulating SV strains in environmental (water) samples and clinical Studies which met the inclusion criteria (n=45) samples from communities in low and middle income coun- tries (particularly rural settings). eTh time-frame chosen was 2004 to 2017 because of the availability of published data on human SV within the low and middle income countries. Studies on stool samples (n= 41) 2. Methodology Study on stool & environmental sample (n=1) Two literature searches were carried out. The first literature Studies on environmental sample (n=3) search was performed using the terms: calicivirus, sapovirus, and developing countries, as listed by National Institutes of SV positive studies, which did Health PUBMED library and ScienceDirect. A second litera- not identify genogroups (n=11) ture search was independently done for each of the 139 “devel- oping” countries accessed from the list published by the Soci- ety for the Study of Reproduction (http://www.ssr.org). Fur- Studies which identified SV genogroups (n=33) thermore, the identified countries were then assessed accord- ingtothe 2018WorldBankanalyticalclassicfi ation report Figure 1: Schematic diagram showing search process for selection (http://datahelpdesk.worldbank.org/knowledgebase/articles/ of studies reported. 906519). For a successful search, each of the countries' names was combined with the following keywords: cali- civirus, sapovirus, enteric viruses, and gastroenteritis. Studies selection based on the selection criteria (Figure 1), a total of identified by the search terms were selected for inclusion in 45 studies met the inclusion criteria. From 45 publications, the review based on the following inclusion criteria: 41 reported on clinical (stool) samples, 3 on environmental (a) Studies limited to human SV detected in clinical (water) samples, and 1 on both. Of the 42 studies conducted specimen and environmental water samples, reported on clinical specimens, 66.7% (n=28) were done in hospi- in the 21st century. talised patients, 23.8% (n=10) in outpatients, and 9.5% (n=4) (b) SV studies using laboratory molecular techniques in both hospitalised and outpatient settings. including nested-PCR (nPCR), real time-PCR (RT- PCR), and RT-multiplex PCR. 3.1. SV AgeDistributioninHuman Populations. The majority of studies (78.6%; 33/42) investigated SV in children less than Studies were excluded from the review if SV was detected 5 years of age and a further 19% (8/42) included all ages. in other mammalian species or animals or if the study was However, only a single study investigated SV in adults with conducted in high income countries. In case of duplication diarrhoea or acute gastroenteritis. of studies by authors, only one article was included. Data was extracted from each selected study when 3.2. Seasonality. eTh detection of SV from clinical samples provided: country name and its economic status (i.e., low based on seasonality was reported in only 14.3% (6/42) of income, lower, and upper middle income) as per the analyti- the studies. eTh majority (42.9%, 18/42) of the studies did cal classification report by World Bank, study setting (hospi- not report on the time-frame of detection, 38% (16/42) of talised, outpatient, and environment), study population (age the studies showed inconsistent time-frame of detection, and group), population size, duration of the study, diagnostic 4.8% (2/42) of the studies showed detection throughout the method used, number of samples tested for SV (including year. Studies investigating SV in water sources in South Africa their genogroups and genotypes), rfi st author, and year of (SA) did not detect any seasonal peaks. publication (Tables 1, 2 and 3). Five studies reported on samples collected within a period The difference of SV data in middle and low income of 2 to 4 months, and these cases were not defined as countries was analysed for statistical significance by Student’s outbreaks, while the duration period of sample collection for t-test using the simple interactive statistical analysis (SISA) at other 40 studies ranged over periods from 1 year to 5 years. http:home.clara.net/sisa. Result with P< 0.05 was considered significant. 3.3. Sapovirus Detection and Genotyping. From the 42 included studies, 41 of these reported SV positive cases while 3. Results only one study on adults reported negative results (Tables A total of 138 articles published from 2004 to 2017 were 1 and 2). Mixed infection of SV with bacteria and/or other identified from 19 low and middle income countries. Aer ft enteric viruses was identified in 19.5% (8/41) of the studies, a Advances in Virology 3 fi fi fi Table 1: Summary of human SV detection from 33 studies (stool samples) conducted in 14 non-African low and middle income countries. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Study setting Genotypes of year  population size study incidence) 2.7 % SV Lower middle Infants/ From 2004 to Oct 2004 – Jan 2005, Bangladesh 917 HP with AGE RT-PCR (All in<3yrs of age) Dey et al [20] income Children 2005 Sept 2005 SV-GI.1, GI.2 15/305 (4.9%), mixed From March March, May - infection of SV and Astv in Children 305 HP severe GE to September RT-PCR Aragao et al [21] September 1sample SV-GII.1, SV-GI.1, SV-GI.2 OP (81 = diar; From April Children (0 – 2 of 81: 2.5% SV (GI.1, 159 78 = 2008 to July February, April RT-PCR Aragao et al [22] 10 yrs GII.2) non-diar) 2010 From October Children Day Care RT- multiplex 25/539 (4.6%) SV, de Oliveira et al [23] 539 2009 to Not dened Upper middle (6-55 mn old) (Healthy) PCR SV-GI.1, GI.3 Brazil October 2011 income 12/341 (3.5%) [/–HP, HP Quantitative Children, 212 From 2012 to / – OP]. OP Not dened real-time Fiorettietal[24] outpatients 129 2014 SV-GI.1 dominant, GI.2, With AGE PCR (qPCR) GI.6, GII.1, GV.1 426 From January Children 6/156 (3.8%), (156 of<3yrs HP with AGE 2010 to Aug & Sept RT-PCR Reymao et al [25] < 10yrs SV-GI.1, GI.2, GII.2, GII.4 tested) October 2011 From 1990 t0 9/172 (5.2%) Children 172 Community Not defined Nested PCR Costa et al [26] 1992 SV-GI.1, GI.7, GII.1, GV.2 9/477: 1.89% SV (<24 OP with acute month children), mixed From August Children (477)/ infection of SV & AdV in 1 500 to November Aug–Nov2010 RT-PCR Ren et al [27] <5yrs old persistent (23) sample, diar SV-GI dominant, SV-GII & SV-GIV Upper Middle China [9/412] 2.2% SV single income infection, Co-infection: From August 2/412 ETEC with SV, 1/412 Patients (1mn HP & OP with 2014 to Salmonella sp with SV, 412 Not dened RT-PCR Shen et al [28] –78yrs) AGE September 1/412 Salmonella sp with SV &AdV Genogroups not defined 4 Advances in Virology fi fi Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Method used Reference Classification as Study Population Duration of or defined period of Study setting Genotypes of year  population size study incidence) From August 23/226 (39%), mixed Multiplex India (New Lower middle Children 2000 to infection in 5 samples Rachakonda et al 226 HP with AGE Not dened two-step Delhi) income <10yrs December {NV-GII and SV-GI} [29] RT-PCR 2001 SV-GI[22],GII[1] From 2008 to 6/200 (3%), Parsa-Nahad et al Children 200 HP with AGE Winter and in fall RT-PCR 2009 SV-GII [30] Upper middle Patients (3 mn Iran 11.9% SV (patients with income -69yrs;mean From May to 42 HP with AGE May – July 2009 RT-PCR <5yrs of age) Romani et al [31] 15.3yrs July 2009 SV-GI.2 Lower middle From July to 1/36 (2.8%) pos for SV Hansman et al Mongolia Infants 36 households Jul–Aug 2003 RT-PCR income August 2003 SV-GI [11, 12] 57/330 (17%): HP =  % From (175 HP; 155 Nov 2009- Feb/Mar [ ], OP = % Lower middle Children September Real-time Nicaragua 330 OP), with 2010, May-Aug/Sept [/ ]. Bucardoetal[32] income <5yrs 2009 to PCR AGE /diar 2010 SV-GI, GII, GIV{HP: GI.1, October 2010 GI.2; OP: GII.2, GII.3 13.9% SV detection (12.3% 122 Pos: Infants From 1990 to SV mono-infections, 1.6 Enteric HP with AGE Mar, Aug - Oct RT-PCR Phan et al [33] <6to>35 mn 1994 mixed infection – AstV & Viruses SV), SV-GI Lower middle Pakistan 1990: Aug, Sept, Oct income Infants & 1991:Jan,May,Jul, 3.2 % SV children<1 From 1990 to Oct RT-PCR 517 HP with AGE SV-GI dominated, followed Phan et al [34] mn – 5yrs 1994 1992:Mar,Aug,Sep by GII, and GIV 1993: Sep 1994: Apr, July From August Papua New 4/199 (2%) SV, Lower middle Children 2009 to Guinea 199 HP with AGE Not dened RT-PCR Soli et al [35] Genogroups not defined income <5yrs November (Goroka) 2010 Advances in Virology 5 fi fi fi Th Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Genotypes Study setting of year  population size study incidence) 9.0% overall: Quantitative ∗. % [ /] reverse diarrhoeal – SV-GI/1/2/6/7, Upper middle Children 300 non-diar, From 2007 to Peru 599 Four seasons transcription- GII.1/2/4/5, GIV, GV/1; Liu et al [36] income <2yrs 299 diar 2010 real-time ∗ . % [ /] PCR (qPCR) non-diarrhoeal – SV-GII.5, GIV 29/417 (7%) detection, (co-infection in 10/29: 6/10 From June Lower middle Children Real-time with RV, 2/10 with NV, 2/10 Philippines 417 HP with AGE 2012 to Not dened Liu et al [1, 2] income <5yrs PCR with AstV). August 2013 SV-GI.1, GI.2, GII.1, GII.4 &GV From 15%: 11% single infection, 80 randomly November 4% mixed infection – NoV Infants HP with AGE Nov2002–April2003 RT-PCR Guntapong et al [37] selected 2002 to April &SV), 2003 SV-GI 3/248 (1.2%) SV- single Children From 2002 to 248 HP with AGE Not dened RT-PCR infections Khamrin et al [38] <5yrs 2004 SV-GI [GI.1 &GI.2], GIV 25%, mixed infection I 1 From May Jun-Jul, Jan-Mar, sample (NV-GI and SV) Children 296 HP with AGE 2000 to RT-PCR Malasao et al [39] May-Jul, Mar. SV-GI.1, GI.4, GI.5, GII.1, March 2002 GII.2 From January HP with Early summer: March 0.8% SV All age groups 273 2006 to RT-PCR Kittigul et al [40] Upper middle AGE/diar &April SV-GII/3 Thailand February 2007 income Children January to 5/147 (3.4%) SV HP with (Neonate to 147 December Not dened RT-PCR SV-GI [GI.2, GI.1, GI.5] Khamrin et al [41] AGE/watery 5yrs old) 2005 dominating, SV-GII.3 January to Pediatric RT-multiplex 5/160 (3.1%) SV Chaimongkol et al 160 HP with AGE December roughout the year Genogroup not defined patients PCR [42] In 2007, and Children 2007:Feb,Sept,Oct. Semi-nested 7/567 (1.2%), Chaimongkol et al 567 HP with AGE from 2010 to <5yrs &2010: Dec RT-PCR SV-GI.1 [43] Adult (15yrs – RT- multiplex 332 HP with diar Year 2008 Not defined No SV detected Saikruang et al [44] 90yrs) PCR 1.1% SV, mixed infection of NoV-GII & SV in 2 From 2006 to Pongsuwanna et al Patients 1141 HP with AGE May - July RT-PCR samples 2008 [45] Genogroup not defined 6 Advances in Virology fi Table 1: Continued. World Bank Study setup Prevalence (seasons Rate of Detected Country Classification as Study Population Duration of or defined period of Method used Reference Genotypes Study setting of year  population size study incidence) From HP with acute December 1/448 (0.2%) SV Children 448 sporadic 1999 to Not dened RT-PCR Hansman et al [46] SV-GI gastroenteritis November 0.8% SV (0.4% From October monoinfection, 0.4% Paediatric HP with viral 2002 to Oct 2002 – Sep 2003, 1010 RT-PCR Nguyen et al [47] coinfection), patients AGE September Rainy season (July) Genogroup not defined From Lower middle Vietnam income December Pediatric 502 HP with AGE 2005 to Dry season RT-PCR 1.2% SV Nguyen et al [48] November 1.4% SV From SV-GI and SV-GII Children November Cooler months (Oct – Real-time 501 HP with AGE Co-infection of (NoV & Trang et al [49] <5yrs 2007 to Feb) RT-PCR SV) in 1 sample, of (NoV, October 2008 SV, and RV) in 1 sample Independent See information From January States of the Real-time 16/495 (3.2%) below describing Children 495 HP with AGE to December Jan - Mar, May – Aug Chhabra et al [50] former Soviet PCR SV-GI.1 dominating the States 2009 Union HP = hospitalised patient; OP = outpatient; AGE = acute gastroenteritis; mn= month; yr(s) = year(s); diar = diarrhoea; SV = Sapovirus; G (I-IV) = genogroup (I-IV) ∗Independent States of the former Soviet Union refers to Armenia, Azerbaijan & Belarus (uppermiddleincomestatus), and Georgia, Republic of Moldova & Ukraine (lower middle income status). Advances in Virology 7 fi fi fi fi fi fi Table 2: Summary of human SV detection from 9 studies (stool samples) conducted in 5 African countries. World Bank Study setup Prevalence (seasons or Method Country Classification defined period of Rate of Detected Genotypes Reference Study Duration of used Population size Study setting as of year  population study incidence) 9%: 27/263 (10.3%){5/27 = 263 diarrhoeal, From November hospitalised, 22/27 = Urban area (HP Real-time Ouedraogo Children 50 2011 to Not dened non-hospitalised}& 3/50 (6%) &OP) RT-PCR et al [51] non-diarrhoeal September 2012 SV-GII [GII.2, GII.1, GII.3], SV-GI.2 Burkina 56/309 (18%) [mixed infection: Low income Faso with RV 25/56, with NV 5/56; From May 2009 Real-time single infection 20/56] Matussek Children<5yrs 309 diarrhoeal Not defined Not dened to March 2010 PCR Genogrouping{34/56}:SV-GI et al [16] [GI.1, GI.4], GII [GII.1, GII.4, GII.6], GIV.1 & GV.1 Government 213 diarrheic From June to 9/213 (4.2%) Sisay et al Ethiopia Lowincome All agegroups Health Care June-sept 2013 RT-PCR samples September 2013 One sequenced (SV-GII.1) [52] Centre 5%: 13/334 (4%) and 31/524 (6%) Lower middle 334-Lwak & From June 2007 Shioda et al Kenya All age groups Clinics with diar Not dened RT-PCR SV income 524-Kibera. to October 2008 [3] Genogroups not defined 10/245 (4.1%) incl. one HP Not defined Real-time Mans et al Paediatric<13yrs 245 Year 2008 Mixed infection with NV gastroenteritis RT-PCR [53] Genogroups not defined 16/190 (8.4%): (1 - 62yrs: mean From July 2007 Patients 1mn to 94 diar Bio-wipes from Real-time Mans et al 24yrs) to December Not dened 87yrs mean 14yrs 93 non-diar rural households RT-PCR [54] Genogroups not defined 3unknown South Upper middle 221 were characterised Selected) 296 of Africa income From April 2009 (genotyped) 477 SV-Pos HP with Nested Murray et Children to December Not dened SV-GI [GI.1 – GI.3, GI.5, GI.6, (for gastroenteritis PCR al [55] 2013 GI.7], SV-GII [GII.1 – GII.7], characterisation) SV-GIV 238/3103 (7.7%) SV From 2009 to Higher in Summer & Real-time Page et al Children<5yrs 3103 HP diar Genogroups not defined 2013 Autumn (Nov to Apr) PCR [56] 6/788 (0.8%) [Mixed infection: 788 From January RT-PCR Sdiri- Lower middle Consulting for with RV 2/6; single infection Tunisia Children [408 HP, 380 2003 to April Not dened Primer Loulizi et al income AGE 4/6]. Positive from OP samples OP] 2007 Noel, 1997 [57] SV-GI.1 HP = hospitalised patient; OP = outpatient; AGE = acute gastroenteritis; mn= month; yr(s) = year(s); diar = diarrhoea; SV = Sapovirus; G (I-IV) = genogroup (I-IV). 8 Advances in Virology Table 3: Summary of human SV detection from 4 studies (water samples) conducted in low and middle income countries. World Bank Classification as Samples Prevalence Rate of Country Method used Reference of year  (season) detection Type Size Duration Quantitative From 2012 Summer and Fioretti et al Brazil Upper middle income Wastewater 156 real-time 51/156 (33%) to 2014 Autumn [24] PCR (qPCR) May, Aug, From 2009 Nov (2009); 48/99 Murray et al River water 99 RT-PCR to 2010 Jan, April (48.5%) [58] (2010) From August August South Real-Time Murray et al Upper middle income Wastewater 51 2010 to (2010), June, 37/51 (72.5%) Africa qPCR [59] December July (2011) Water January January and Real-Time Murray and (various 10 and March 8/10 (80%) March 2012 PCR Taylor [60] source) 2012 SV single strain was identified in 36.6% (15/41) of the studies, 4. Discussion and mixed strains of SV were identified in 43.9% (18/41) of This review provides a summary of studies conducted in the studies. From the 41 studies, only 31 studies reported SV developing countries on the detection of human SV. Only detection with identification of the genogroups/genotypes. 45 (41 stool samples, 3 water samples, and 1 both stool Overall detection of SV strains showed SV-GI.1 and GI.2 and water sample) studies satisfied the inclusion criteria as the most dominant[90%(28/31)] strain from different of this review highlighting the importance for systematic settings of studies, followed by SV-GII.1, GII.2, GII.3, and surveillance monitoring human SV circulating in developing GII.4 with the least detection of SV-GIV strain and –GV countries (rural and urban communities). Very little is known (GV.2) strain. No study showed the occurrence of SV- about the contribution of human SV to diarrhoeal disease in GIV as a single detection but only in mixed infection developing countries; this is reflected in the fact that reported cases. studies were only from 19 identified countries which include The prevalence rate of SV from the 41 documented 5 African countries, namely, Burkina Faso, Ethiopia, Kenya, studies in low and middle countries was 6.19% with a range South Africa, and Tunisia (Table 2). A total of 78.6% (33/42) from 0.2% to 39%. Further breakdown showed significant studies reported on children≤5yearsofagefromthe col- difference ( P =0)inSVprevalenceratebetween lowincome lected data, highlighting the role of SV in diarrhoeal disease (10.40%) and middle income (5.86%) countries. Although amongst children in the developing countries. Hence, SV and data on the prevalence of SV in African countries is limited, other emerging enteric viruses, being underappreciated, can thus far, eight studies have been conducted in urban settings. be an important cause of Norovirus negative outbreaks as Detection of SV from children in Africa is recorded with different incidence rates: in Tunisia [0.8%] [57], Burkina reported by Lee and colleagues [61]. In addition, since it is dicffi ulttoculture humanSVoncelllines[13], specialised Faso [18%,10.3%,respectively][16, 51], andSouth Africa [4.1%, 7.7%, respectively] [53, 56]. The prevalence of SV in molecular laboratories are needed for the investigation of all ages was reported from South Africa [8.4%] [54], Ethiopia such virus in the developing countries. Because of lack [4.2%] [52], and Kenya [4%] [3]. A predominance of SV-GIV of funding and skills, the prevalence of enteric viruses is (53/221, 24%) was noted in the South African study done on underreported in Africa and other developing countries [62] stool samples from hospitalised children with gastroenteritis Most of the studies (66.7%; 28/42) were done in hospi- [55]. talised patients, and this might be due to the fact that SV Only 8.9% of studies reported SV in the environmental infection sometimes leads to hospitalisation as illustrated and waste water samples from low and middle income from other studies [49, 63]. GEMS study reported SV countries. The detection of SV-GI, SV-GII, and SV-GIV has amongst other enteric pathogens to have been associated with been reported from polluted water sources by wastewaters moderate to severe diarrhoea in developing countries [64]. and also on samples collected from treatment plants within The Millennium Development Goals (MDG) 2015 report selected areas of SA [58–60]. Sapovirus genogroups I and II shows disadvantaged settings being vulnerable as compared were identified from river water samples, with detection rate with the advantaged or developed settings, highlighting the of 48.5% (48/99) [58], while, in Brazil, SV-GI (genotypes 1 eeff ctiveness and affordability of treatments, and improved and 2) were detected (33%, 51/156) from the wastewaters [22], service delivery and political commitment playing a role in Table 3. such settings. eTh statistical analysis of this review similarly Advances in Virology 9 showed a significant difference in the prevalence of SV in low public health intervention strategies. Furthermore, detection income than in middle income countries (P=0). of enteric viruses (such as SV) in environmental samples eTh circulation of SV genogroups shows variability, with gives awareness of the circulation of infectious viral particles SV-GI and SV-GII detected frequently, while SV-GIV and within the population and health-hazards which might be SV-GV are rarely detected comparing to other genogroups associated with the environment. eTh predictable eect ff s [16]. An African study (Burkina Faso) reported SV-GII as the of human waste disposal, water quality, and high rate of predominated strain, mostly in outpatients with diarrhoea immunocompromised society have been a big concern in (81.5%: 22/27), suggesting that this genogroup may be less low and middle income countries, but there are still few virulent and require fewer hospital admissions. However, documented reports on the detection of SV from environ- additional studies on outpatients will have to be conducted mental samples. This is highlighted by the finding of this to conrm fi this observation. Although the detection of SV- study with high prevalence of SV in low income countries. GII is seen in diarrhoeal samples, it might be less virulent to The survival and development of children depend on good cause severe symptoms leading to hospitalisation of patients, hygiene practices and use of clean drinking and domestic unlike SV-GI which is commonly known to be associated water on daily basis [4]. Monitoring of genetic diversity of with severe symptoms and frequently detected in patients the current circulating or emerging SV genogroups, possible presenting with gastroenteritis [16, 32]. eTh detection of SV water-borne transmission, and possible zoonotic infections (GI, GII, GIV, and GV) in gastroenteritis outbreak cases has amongst the communities is critical, and studies which can been reported in high income countries, however with less show the transmission of SV between the environment(s) detection rate of SV-GII in both cases [14, 17, 61, 65]. (especially river water), domestic animals, and human should Human SV infections cases relating to acute gastroenteri- be considered, and the role that SV plays in diarrhoeal tis in people of all ages have been identified worldwide [14]. diseases [69]. Notwithstanding the potential selection biases present based on the studies available for inclusion, this review shows that 5. Conclusion the prevalence in children may be higher than in adults in low and middle income countries. In addition, the GEMS study in This review found substantial evidence of SV proportion associated with diarrhoeal disease in low and middle income low and middle income countries highlights diarrheal disease countries. However there is limited data reporting the detec- in children as a leading cause of illness and death and also increasing the risk of delayed physical and intellectual devel- tion of circulating SV strains. eTh refore systematic surveil- lance of SV circulation within the communities in low and opment [66]. It has been reported that sporadic and outbreak cases caused by enteric viruses spread mainly by person- middle income countries is needed to assess sufficiently its to-person contact, contaminated surfaces or objects, and role in diarrhoea disease. contaminated water or food [67]. eTh refore children are more vulnerable than adults within such exposed environment, Conflicts of Interest probably because of immune system development. However, eTh authors declare that there are no conflicts of interest previous studies noted that gastroenteritis symptoms are regarding the publication of this paper. usually self-limiting, and patients usually recover within a couple of days depending on the individual immune’s response [49, 63]. Adults are likely to consider self-treatment References by oral rehydration solution (ORS) which is the safe, effective, [1] L. Liu, S. Oza, D. 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