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PLOS Neglected Tropical Diseases logoLink to PLOS Neglected Tropical Diseases
. 2019 Jan 29;13(1):e0007081. doi: 10.1371/journal.pntd.0007081

Epidemiology of West Nile Virus in the Eastern Mediterranean region: A systematic review

Sana Eybpoosh 1, Mehdi Fazlalipour 2, Vahid Baniasadi 2, Mohammad Hassan Pouriayevali 2, Farzin Sadeghi 3, Abbas Ahmadi Vasmehjani 4, Mohammad Hadi Karbalaie Niya 5, Roger Hewson 6, Mostafa Salehi-Vaziri 2,7,*
Editor: Hans-Peter Fuehrer8
PMCID: PMC6368338  PMID: 30695031

Abstract

Background

West Nile Virus (WNV), a member of the genus Flavivirus, is one of the most widely distributed arboviruses in the world. Despite some evidence for circulation of WNV in countries summarized by the World Health Organization as the Eastern Mediterrian Regional Office (EMRO), comprehensive knowledge about its epidemiology remains largely unknown. This study aims to provide a concise review of the published literature on WNV infections in the Eastern Mediterranean Regional Office of WHO (EMRO).

Methodology/principal findings

A systematic review of WNV prevalence studies on humans, animals and vectors in the EMRO region was performed by searching: Web of Science, Science Direct, Scopus, PubMed, Embase and Google Scholar. Finally, 77 citations were included, comprising 35 seroprevalence studies on general population (24460 individuals), 15 prevalence studies among patients (3439 individuals), 22 seroprevalence studies among animals (10309 animals), and 9 studies on vectors (184242 vector species). Of the 22 countries in this region, five had no data on WNV infection among different populations. These countries include Kuwait, Bahrain, Oman, Syria and Somalia. On the other hand, among countries with available data, WNV-specific antibodies were detected in the general population of all investigated countries including Djibouti (0.3–60%), Egypt (1–61%), Iran (0–30%), Iraq (11.6–15.1%), Jordan (8%), Lebanon (0.5–1%), Libya (2.3%), Morocco (0–18.8%), Pakistan (0.6–65.0%), Sudan (2.2–47%), and Tunisia (4.3–31.1%). WNV RNA were also detected in patient populations of Iran (1.2%), Pakistan (33.3%), and Tunisia (5.3% –15.9%). WNV-specific antibodies were also detected in a wide range of animal species. The highest seropositivity rate was observed among equids (100% in Morocco) and dogs (96% in Morocco). The highest seroprevalence among birds was seen in Tunisia (23%). In addition, WNV infection was detected in mosquitoes (Culex, and Aedes) and ticks (Argas reflexus hermanni). The primary vector of WNV (Culex pipiens s.l.) was detected in Djibouti, Egypt, Iran and Tunisia, and in mosquitoes of all these countries, WNV was demonstrated.

Conclusions

This first systematic regional assessment of WNV prevalence provides evidence to support the circulation of WNV in the EMRO region as nearly all studies showed evidence of WNV infection in human as well as animal/vector populations. These findings highlight the need for continued prevention and control strategies and the collection of epidemiologic data for WNV epidemic status, especially in countries that lack reliable surveillance systems.

Author summary

West Nile Virus (WNV) is a mosquito-borne Flavivirus belonging to the Flaviviridae family, which is endemic in a vast geographical area, including the EMRO region. However, the epidemiology of WNV in the EMRO region remains poorly understood. To address this gap, we performed a systematic review on WNV prevalence studies conducted on human populations, animals and vectors across Eastern Mediterranean countries. Our review indicated the infection of most investigated human, animal and vector populations with WNV; however, the paucity of epidemiological data underline the need for integrated surveillance programs as well as continued deployment of prevention and control strategies.

Introduction

West Nile Virus (WNV) is one of the most widely distributed arboviruses in the world, and a pathogen of public health significance in both humans and animals [1]. This mosquito-borne virus has been classified in the genus Flavivirus within the family Flaviviridae [2]. In nature, WNV is maintained in a zoonotic transmission cycle between birds and mosquitos, principally the Culex species. Susceptibility to WNV infection has also been indicated for many other vertebrate hosts including mammals, birds, reptiles, and amphibians [3]. Equines and humans are incidental “dead-end” hosts who do not play a role in the transmission cycle of the virus. However, equines and humans may manifest sever disease or death as a consequence of infection [4]. Since the first discovery of the virus in 1937 in the West Nile district of Uganda [5], it has undergone a substantial geographical migration, and spread around the globe. Infection with WNV was first identified in an EMRO country (Sudan) in the 1940s. Since then, infection with the virus has been reported in Egypt (1950s), Iran (1970s), and subsequently in several other countries across the region [6]. The prevention and control efforts substantially rely on effective surveillance of the infection in birds, vectors, animals, and humans. Despite several studies on different aspects of WNV epidemiology in the EMRO region, there are still many unknowns about the circulation of the virus and the driving factors of outbreaks [6, 7]. Understanding the epidemiology of WNV in the EMRO faces a number of challenges including inadequate knowledge of physicians about the nature of the disease, misdiagnosis of other common infectious diseases due to similarity in clinical presentations, poor diagnostic infrastructures and the absence of confirmatory assays for serological tests, and lack of a comprehensive and progressive monitoring and surveillance system in majority of countries. The latter has resulted in a gap in knowledge regading the prevalence of WNV infection in the EMRO region. Therefore, we designed a systematic review to provide a clear and comprehensive presentation of the virus prevalence distribution among human and animal populations as well as infection rate in vectors of the region, based on available data.

Methods

Data sources and search strategy

Articles were screened and selected according to the PRISMA criteria [8]. The PRISMA checklist completed for this review is presented in S1 File. We made an electronic literature search through Web of Science, Scopus, PubMed, Google Scholar, and Index Medicus for the Eastern Mediterranean region database (IMEMR) using different combinations of the following keywords ‘West Nile virus, West Nile Fever, WNV’ and the name of the EMRO countries as: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, United Arab Emirates, and Yemen (S2 File). All databases were searched for English-language original articles published from database inception to January 30, 2018. Choosing multiple sources for article search we aimed to enhance our sensitivity in finding relevant articles. To find citations that were not indexed in our target databases, we reviewed the reference lists of relevant articles.

Review selection

Studies identified through electronic and manual searches were listed in EndNote software (EndNote X7, Thomson Reuters). After exclusion of duplicate citations, two authors (MF, FS) independently reviewed titles and abstracts according to the research question. Relevant studies were obtained in full, and assessed for eligibility and risk of bias as described below. All original articles from peer-reviewed scientific journals with a cross-sectional or survey design that estimated the prevalence of WNV infection in humans, animals, or infection rate in vectors were potentially eligible for inclusion in this review. Relevant studies whose abstract was available but their full-text was not (even after contacting the authors via e-mail), were kept in this review in order to present all available data. Studies from outside of the EMRO region were excluded. Any disagreements between the review team were resolved through discussion.

Risk of bias assessment

The risk of bias in primary studies was assessed following the Cochrane approach [9]. We also considered individual studies’ sample size (precision) as a criterion to assess risk of bias, as proposed by Humphre, et al. [10]. Therefore, we evaluated each WNV prevalence study in three domains: 1) sampling method, 2) response level (the proportion of subjects who accept to participate in the study), and 3) type of assay used for the detection of WNV. Each study was considered to have a low risk of bias if: 1) it used probability-base/random sampling methods, 2) maintained participants’ response level at ≥80% [11, 12], or 3) it employed viral neutralization testing (VNT) for a prevalence study on the general population or used biological tests including viral genome detection and virus isolation from infected individuals. Studies were classified as having unclear risk of bias for a given domain if they did not provide information for that specific domain. Use of probabilistic sampling methods was only evaluated for studies on the general population, because acute infection studies included individuals attending to healthcare facilities. For studies that were conducted on blood samples collected and stored from blood donors, response rate criteria were not evaluated. Studies on human subjects were considered to have high precision if their sample sizes were ≥ 100 [13]. Moreover, in the studies on WNV vectors, minimum infection rates (MIR), that were calculated for samples of ≥ 1000 specimens, were considered as a reliable representation of the true infection rate in the vector population [14, 15].

Data extraction

Data was extracted from the selected studies using a researcher-made and piloted data extraction form in excel. For studies on human and animal subjects we extracted data on: first author, year of publication, year of implementation, country, city/governorate, sample size, participants’ age and sex (for human subjects only), animal species (for studies on animals), assay type, and estimated assay-based WNV prevalence. For studies on vector populations, further data was extracted including vector species, number of species (vectors) tested, collection methods, number and size of the pools as well as the number of positive pools for each species. WNV minimum infection rate (MIR) for each species was calculated by dividing the number of positive pools by the total number of specimens tested for that specific species and multiplied by 1000. When data was available, assay-specific MIRs were calculated and reported.

Results

Search results

Database search resulted in 3298 records. After removal of duplicates, we initially screened the title and abstract of 2667 records, 2488 of which were excluded as they were irrelevant to this review. The remaining 179 papers were reviewed in full, of which 77 eligible reports on the prevalence/MIR of WNV covering 17 countries in the EMRO region were included in this systematic review. We identified two relevant citations by reviewing the reference list of these relevant studies [16, 17]. Fig 1 shows the literature search process. The full-text of five studies could not be obtained even after contacting the authors [1822]. These studies were kept in this review to present all available data to the readers. All included studies on WNV entailed 27899 individuals (24460 general populations and 3439 patients), 10309 animals, and 184242 vector species.

Fig 1. Flow diagram of article selection for West Nile prevalence in human and animals, and infection rate in vectors of the EMRO region.

Fig 1

Four citations included data on more than one subject categories (i.e., humans, animal species, and vectors).

Risk of bias assessment results

A summary of the risk of bias assessment results is shown in Table 1. In brief, most human studies (28 out of 35) contained sample sizes of ≥100 participants, yielding a high precision in the reported prevalence measure. Thirty out of thirty-five studies on the general population reported their sampling strategy, fourteen of which utilized some forms of random sampling, and hence, had low risk of bias at this domain. In most studies on the general population (24 out of 35), risk of bias assessment was affected by unclear reporting in the ‘response rate’ domain. Six studies were performed on volunteers or on blood specimens stored in national reference laboratories or blood transfusion centers, and hence, were not subjected to risk of bias assessment in the ‘response rate’ domain. Viral neutralization test was performed in 40.0% and 13.3% of prevalence studies on the general and patient populations, respectively, which entails a low risk of bias for the assays used.

Table 1. Precision and risk of bias assessment for West Nile virus prevalence measures in the EMRO region.

Author, Year Country Sampling Method¥ Risk of bias Precision Ref.
In sampling¥ In response rate In assay selection
General population
Andayi, 2014 Djibouti Random Low Unclear Low High [23]
Faulde, 2012 Djibouti Conv. Low Low (100%) High Low [24]
Youssef, 2017 Egypt Conv. High Unclear High High [25]
Soliman, 2010 Egypt Random Low Unclear Low High [26]
Darwish 1996 Egypt Unclear Unclear Unclear High High [22]
Corwin, 1993 Egypt CS Low Low (93%) High High [27]
Corwin, 1992 Egypt Random Low Low (78%) High High [28]
Darwish, 1975 Egypt CS Low Unclear High High [29]
Taylor, 1956 Egypt CS Low Unclear Low High [30]
Aghaie, 2016 Iran Conv. High Unclear High High [31]
Meshkat, 2015 Iran MSCS Low Unclear High High [32]
Chinikar, 2013 Iran Unclear Unclear Unclear High Low [33]
Sharifi, 2010 Iran Conv. High Low (100%)* High High [34]
Saidi, 1976 Iran Random Low Unclear Low High [17]
Saidi,1974 Iran Random Low Unclear NA High [16]
Naficy, 1970 Iran Unclear Unclear Unclear Low High [19]
Barakat, 2016 Iraq Conv. High Low (100%)** Low High [35]
Batieha, 2000 Jordan Conv. High 56% High High [36]
Gallian, 2010 Lebanon Conv. High Unclear Low High [37]
Garabedian, 1971ǂ Lebanon Unclear Unclear Unclear High High [18]
Shaibi, 2017 Libya Random Low Unclear High High [38]
El Harrak 2016ǂ Morocco Conv. High Unclear Low High [39]
El Rhaffouli, 2013 Morocco Conv. High Low (100%)* Low High [40]
El Rhaffouli, 2012 Morocco Random Low Low (100%) Low High [41]
Niazi 2017 Pakistan Random Low Unclear High High [42]
Sugamata, 1989 Pakistan Unclear Unclear Unclear Low High [43]
Sugamata, 1988 Pakistan Unclear Unclear Unclear Low Low [44]
Darwish, 1983 Pakistan Conv. High Unclear High Low [45]
Hayes, 1982 Pakistan Conv. High Low (100%)** Low High [46]
Yousof 2017 Sudan Random Low Low (100%)* High Low [47]
Farnon 2010 Sudan Conv. High Unclear Low Low [48]
Salim, 1973 Sudan Conv. High Unclear Low High [49]
Taylor, 1956 Egypt CS Low Unclear Low High [30]
Smithbur, 1942 Anglo-
Egyptian
Sudan
CS Low Unclear Low High [50]
Riabi, 2010 Tunisia Conv. High Low (100%)** Low High [51]
Alfaresi, 2008 UAE Conv. High Unclear High Low [52]
Patients
Elyan, 2014 Afghanistan NA NA Unclear High High [53]
Darwish, 1987 Egypt NA NA Unclear High Low [54]
Mohammed, 1970 Egypt NA NA Low (100%) High High [55]
Abdel Wahab, 1970ǂ Egypt NA NA Unclear NA High [20]
Chinikar, 2012 Iran NA NA Unclear Low High [56]
Yaqub,2017 Pakistan NA NA Low (100%) Low High [57]
Khan, 2016 Pakistan NA NA 100% High High [58]
Bryan, 1996ǂ Pakistan NA NA Unclear NA High [21]
Igarashi, 1994 Pakistan NA NA Unclear Low High [59]
Depoortere, 2004 Sudan NA NA Low (100%) High Low [60]
McCarthy, 1996 Sudan NA NA Unclear High High [61]
Watts, 1994 Sudan NA NA Unclear High High [62]
Riabi, 2014 Tunisia NA NA Unclear Low High [63]
Feki, 2005 Tunisia NA NA Low (100%) Low Low [64]
Qassem, 2014 Yemen NA NA Unclear High Low [65]

* On blood specimens stored in the blood transfusion center

** On volunteers

ǂ Studies were classified as having “Unclear” risk of bias for a given domain if they did not provide information for that specific domain. These studies were categorized as “Unclear” risk of bias.

¥ Use of probabilistic sampling methods was only evaluated for studies on the general population, because acute infection studies included individuals attending to healthcare facilities. So, risk of bias assessment for the “sampling” domain, was “Not Applicable” (NA) for patients.

On archived samples.

Abbreviations: Conv: Convenience sampling. CS: Cluster Sampling. MSCS: Multi-stage cluster sampling. NA: Not applicable to the field.

WNV prevalence among the general and patient populations of the EMRO region

A total of 50 human prevalence studies for WNV were identified, 35 of which estimated the seroprevalence in the general population. Furthermore, and 15 of them investigated the presence of WNV antibody or genetic material in patients suspected with WNV infection. Human studies covered 14 of 22 countries of the EMRO region, and were published from 1942 to 2017. The highest number of human studies were reported from Egypt (n = 10), Iran (n = 8), and Pakistan (n = 9), most of which targeted the general population. ELISAs were the most commonly used diagnostic method for the general and patient populations. Table 2 presents detailed data for these studies. The geographic distribution of human prevalence studies is also illustrated in Fig 2A and 2B.

Table 2. Summary of human prevalence studies for West Nile virus in the EMRO region (n = 50).

Author, Pub. year Study year Country City/governorate SS Participant characteristics Assay Prevalence (%)
Ref
Male/Female Age range (yrs) IgG ELISA IgM ELISA NT IF HI CF RT-PCR
General population
Andayi, 2014 2010–2011 Djibouti Djibouti 893§ NA NA ELISA, NT 0.6 - 0.3 - - - - [23]
Faulde, 2012 2010–2012 Djibouti Djibouti 10 NA NA IF - - - 60.0 - - - [24]
Youssef, 2017 2013–2014 Egypt NA 160 124/ 36 18–55 ELISA, RT-PCR 55.0 - - - - - 0 [25]
Soliman, 2010 1999–2000 Egypt Total 5965 NA NA ELISA, NT 24.0 - 24.0 - - - - [26]
Fayoum 1593 27.3 - 27.3 - - - -
Sharqiya 1292 13.8 - 13.8 - - - -
Al Arish 202 1.0 - 1.0 - - - -
Nuweiba 675 6.7 - 6.7 - - - -
Qena 2203 35.0 - 35.0 - - - -
Darwish, 1996ǂ NA Egypt Minufiya 178 NA NA ELISA, HI, IF 45.0 - - 26.4 37.6 - - [22]
Corwin, 1993 1991 Egypt Nile 915 356/559 <1–80 ELISA 20.0 - - - - - - [27]
Corwin, 1992 1989 Egypt Nile 437 215/222 8–14 ELISA 3.0 - - - - - - [28]
Darwish, 1975 1969 Egypt Cairo 1133 NA NA HI - - - - 50.0 - - [29]
Taylor, 1956 NA Egypt Egyptian Nile delta 1168 NA NA NT 61 - 61 - - - - [30]
Aghaie, 2016 NA Iran Chabahar 540 514/26 17–65 ELISA,IF 18.0 - - 1.5 - - - [31]
Meshkat, 2015 2011–2012 Iran Mashhad 182 46/136 15–65 ELISA 11.0 - - - - - -
[32]
Chinikar, 2013 2010–2011 Iran Total 300 NA NA ELISA 1.3 - - - - - - [33]
Golestan 90 2.2 - - - - - -
Gilan 70 1.4 - - - - - -
Mazandaran 71 0.0 - - - - - -
Qom 69 1.4 - - - - - -
Sharifi, 2010 2005 Iran Tehran 500 490/10 17–65 ELISA, RT-PCR 5.0 0 - - - - 0 [34]
Saidi, 1976 1971–1975 Iran NA 698 NA NA NT - - 26.6 - - - - [17]
Saidi,1974 NA Iran NA 100 NA NA NA 10.0 - - - - - - [16]
Naficy, 1970ǂ NA Iran NA 2975 NA NA NT, HI 30.0 - - - - - - [19]
Barakat, 2016 2012–2013 Iraq Nasiriyah 397 NA 10–82 NT, IF, HI - - 11.6 14.9 15.1 - - [35]
Batieha, 2000 1998 Jordan Hashimia 261 75/186 ≥ 5 ELISA 8.0 - - - - - - [36]
Gallian, 2010 2006 Lebanon Total 627 74/553 18–59 ELISA,NT 1.0 - 0.5 - - - - [37]
Central Lebanon 500
Bekaa 36
Northern Lebanon 46
Southern Lebanon 45
Garabedian, 1971ǂ NA Lebanon NA 215 NA NA HA, CF NA - - - 0 0 - [18]
Shaibi, 2017 2013 Libya Tripoli 400 277/123 15–78 ELISA 2.3 - - - - - - [38]
El Harrak, 2016 2013 Morocco NA 622 NA NA ELISA, NT - 0 5.6 - - - - [39]
El Rhaffouli, 2013 2012 Morocco Wad-ad-Dahab 250 147/103 <1–80 NT - - 5.2 - - - - [40]
El Rhaffouli, 2012 2011 Morocco Total 499 186/313 31–65 NT - - 11.8 - - - - [41]
Meknes 150 46/104 37–67 - - 4.7 - - - -
Rabat 200 76/124 37–61 - - 12.0 - - - -
Kenitra 149 64/85 31–65 - - 18.8 - - - -
Niazi, 2017 NA Pakistan NA 1860 1847/13 18–57 RT-PCR - - - - - - 0.21 [42]
Sugamata, 1989 1985 Pakistan Karachi 150 NA 6–65 NT - - 53.3 - - - - [43]
Sugamata, 1988 1983 Pakistan Karachi July 33 14/19 NA HI - - - - 55.0 - - [44]
September 48 29/15 NA HI - - - - 65.0 - -
1985 Karachi July 156 122/34 NA NT, HI - - 50.0 - 53.0 - -
October 156 122/34 NA NT, HI - - 54.0 - 59.0 - -
Darwish, 1983 NA Pakistan Karachi, Sind, Punjab 43 NA NA CF - - - - - 11.6 - [45]
Hayes, 1982 1978–1979 Pakistan Chiniot 192 NA 1->61 NT - - 32.8 - - - - [46]
Change Manga national forest 239 NA 1->61 NT, HI - - 38.5 - 33.1 - -
Yousof, 2017 2016 Sudan Khartoum 90 NA NA ELISA 44.4 2.2 - - - - - [47]
Farnon, 2010 2005 Sudan Kortalla 87 37/50 5–44< NT - - 39.1 - - - - [48]
Salim, 1973 NA Sudan Sennar 17 NA <1–40 NT - - 47.0 - - - - [49]
Taylor, 1956 NA Sudan Southern Sudan 350 NA NA NT 40 - 40 - - - - [30]
Smithburn, 1942 1939–1940 Anglo-Egyptian Sudan Total 270 NA 4–75 NT - - 28.9 - - - - [50]
Red Sea coast 23 5–55 - - 13.0 - - - -
Eastern border 75 4–60 - - 33.3 - - - -
White Nile 56 6–75 - - 46.4 - - - -
Kordofan 89 4–68 - - 20.8 - - - -
Southwestern 27 7–40 - - 18.6 - - - -
Riabi, 2010 2003 Tunisia Monastir 742 497/245 18–54 ELISA,NT 15.6 - 4.3 - - - - [51]
Mahdia 102 68/34 19–45 31.1 - 13.7 - - - -
Alfaresi, 2008 2005 UAE UAE 500 - - RT-PCR - - - - - - 0 [52]
Patients
Elyan, 2014 2008–2010 Afghanistan Uruzgon, Helmand, Kandahar, Kabul 913 493/420 20–59 ELISA, NT 30.4 0.5 2.6 - - - - [53]
Mohammed, 1970 1968 Egypt Alexandria Acute sample 120 60/60 3–13 CF, HI - - - - 4.3 0 - [55]
Convalescent sample 48 24/24 NA HI - - - - 14.6 - -
Darwish, 1987 1985 Egypt Cairo Prior infection 55 32/23 >10 HI - - - - 58.0 - - [54]
Acute infection - - - - 1.8 - -
Abdel Wahab,1970ǂ NA Egypt NA 133 NA NA NA 3.7 - - - - - - [20]
Chinikar, 2012 2008–2009 Iran Isfahan 249 126/123 10–81 ELISA, RT-PCR 2.4 0 - - - - 1.2 [56]
Yaquba, 2017 2014–2015 Pakistan Rawalpindi/Islamabad, Lahore, and Faisalabad 480 NA NA ELISA, RT-PCR 1.3 - - - - 3.1 - [57]
Khan, 2016 2015 Pakistan Karachi, Hyderabad, Mirpurkhas, Sukkur 241 NA 10–50 ELISA - 6.6 - - - - - [58]
Bryan, 1996ǂ NA Pakistan NA 570 NA NA NA 33–41 - - - - - - [21]
Igarashi, 1994 1992 Pakistan Karachi 24 NA NA ELISA,RT-PCR - 0 - - - - 33.3 [59]
Depoortere, 2004 2002 Sudan Ngorban, South Kordophan Neurological sequelae 8 7/6 6–84 ELISA, NT 62.5 87.5 6.6 - - - - [60]
Convalescent 5 0 20.0 0.1 - - - -
McCarthy, 1996 1988 Sudan Khartoum 196 NA 1–89 ELISA 60.0 0.3 - - - - - [61]
Watts, 1994 1989 Sudan Karima 185 NA 11–70 ELISA 59.0 - - - - - - [62]
Riabi, 2014 2003 Tunisia Monastir 113 NA NA ELISA, RT-PCR 33.6 - - - - 15.9 [63]
Feki, 2005 1997 Tunisia Sfax 57 50/7 NA ELISA, RT-PCR 52.6 - - - - 5.3 [64]
Qassem, 2014 2013 Yemen NA 42 NA All ELISA - 14.3 - - - - - [65]

§ These individuals are selected from 324 households.

ǂ The data for these studies is driven from articles’ abstract, as their full-text could not be obtained.

Abbreviations: SS: Sample Size, ELISA: Enzyme-linked Immunosorbent Assay, NT: Neutralization Test, IF: Immunofluorescence Assay, HI: Hemagglutination Inhibition Assay, CF: Complement Fixation, RT-PCR: Reverse Transcriptase-Polymerase Chain Reaction, NA: Data was not available, UAE: United Arab Emirates.

Fig 2. WNV infection reported among human and animal populations of the EMRO countries.

Fig 2

A) studies conducted between 2009 and 2017; B) studies conducted before 2009. Black symbols indicate samples with evidence of WNV infection. The exact sampling location and the prevalence values are provided in the Tables 2 and 3. Countries with no qualified study on human or animal populations are colored in gray. ×2: Where more than one study/sampling effort have been done on a particular species in the same geographic area. UAE: United Arab Emirates.

Regarding the general population, WNV antibodies were detected in 11 countries including Djibouti (n = 2, 0.3–60%), Egypt (n = 7, 1–61%), Iran (n = 6, 0–30%), Iraq (n = 1, 11.6–15.1%), Jordan (n = 1, 8%), Lebanon (n = 2, 0–1%), Libya (n = 1, 2.3%), Morocco (n = 3, 0–18.8%), Pakistan (n = 5, 0.2–65%), Sudan (n = 5, 2.2–47%), and Tunisia (n = 1, 4.3–31.1%). Since 2010, seroprevalence of WNV among the general population has been investigated in Djibouti, Egypt, Iran, Iraq, Libya, Morocco, and Sudan among which the lowest and highest median prevalence was found in Iran (median prevalence = 1.4, range: 0–18%; total SS = 1322; 2010–2012), and Egypt (median prevalence = 55%; total SS = 160, 2013–2014), respectively (Table 2).

In addition, the presence of WNV antibody or genetic material in patients was investigated in 15 human prevalence studies. In this regard, seven studies assessed WNV IgM, five of which detected the antibodies in patients’ sera. These studies were from Afghanistan (n = 1, 0.5%), Pakistan (n = 1, 6.6%), Sudan (n = 2, 0.3–87.5%), and Yemen (n = 1, 14.3%). Four studies [56, 59, 63, 64] used both serological and molecular assays to detect WNV IgM as well as WNV RNA in patients’ sera (Table 2).

WNV prevalence in wild and domestic animals in the EMRO region

A total of 22 studies investigated the WNV seroprevalence in animals (Fig 2A and 2B). WNV antibodies were detected in 10 countries, including, Djibouti (n = 1), Iran (n = 4), Jordan (n = 1), Morocco (n = 4), Pakistan (n = 2), Palestine (n = 1), Qatar (n = 2), Saudi Arabia (n = 1), Tunisia (n = 5) and the United Arab Emirates (UAE; n = 1). In these studies, serological evidence of WNV infection was detected in a wide range of domestic and wild animals, including Buffalos (Pakistan, total SS = 33, prevalence = 15.1%), Camels (Morocco, total SS = 2775, prevalence = 8–23%; Palestine, total SS = 35, Prevalence = 40%; Tunisia, total SS = 120, Prevalence = 0–25.8%), Cows (Pakistan, total SS = 45, prevalence = 2.2%), Goats and sheep (Pakistan, total SS = 94, prevalence = 23.9%; Palestine, total SS = 95, prevalence = 14.7%), Dogs (Djibouti, total SS = 91, prevalence = 56.5%; Morocco, total SS = 231, prevalence = 54–96%), Ruminants (Djibouti, total SS = 11, prevalence = 25.3%), Equids (Iran, total SS = 1839, prevalence = 0.8–70.3%; Jordan, total SS = 253, prevalence = 24.9%; Morocco, total SS = 1189, prevalence = 25–100%; Pakistan, total SS = 449, prevalence = 65%; Palestine, total SS = 585, prevalence = 75%; Qatar, total SS = 421, prevalence: 0–27%; Saudi Arabia, total SS = 63, prevalence = 33.5%; Tunisia, total SS = 1473, prevalence = 28.0–45.2%; the UAE, total SS = 750, prevalence = 5.4–28.6%), and different types of wild and domestic birds (Iran, total SS = 519, prevalence = 15%; Morocco, total SS = 346, prevalence = 3.5%; Tunisia, total SS = 434, prevalence = 0.7–23%). Table 3 provides further details on these studies.

Table 3. Summary of animal prevalence studies for West Nile virus in the EMRO region (n = 22).

Author, Pub. year Study year Country City/governorate Species SS Prevalence (%) Ref
ELISA NT IF HI CF
IgM IgG cELISA
Domestic animals
Marié, 2016 2012–2016 Djibouti Djibouti Dog, Ruminant 91 - 56.5 - - - - - [66]
Durand, 2016 2012 Morocco Total Dog 231 - - 62.0 80.0 * - - - [67]
Benslimane - - 54.0 - - -
Kenitra - - 96.0 - - -
Khenifra - - 75.0 - - -
Sidi Slimane - - 94.5 - - -
Touil, 2012 2003 Morocco Total Camel 556 - - - 10.4 - - - [68]
Guelmim (Atlantic littoral) 73 - - - 23.0 - - -
Smara (Sahara) 85 - - - 8.0 - - -
Aousserd (Sahara) 389 - - - 9.0 - - -
2009 Total 836 - - - 13.6 - - -
Oued Draa 157 - - - 12.0 - - -
Laayoune (Atlantic littoral) 397 - - - 15.0 - - -
Smara (Sahara) 282 - - - 12.0 - - -
Darwish, 1983 1983 Pakistan Karachi, Sind, Punjab Total 172 - - - - - - 9.9 [45]
Cow 45 - - - - - - 2.2
Buffalo 33 - - - - - - 15.1
Sheep 46 - - - - - - 23.9
Goat 48 - - - - - - 0
Azmi, 2017 2014 Palestine
Nablus, Jericho, and Jenin Goat, Sheep 95 - - 14.7 - - - - [69]
Camel 35 - - 40.0 - - - -
Hassine, 2017 2016 Tunisia Medenine Camel 87 - - 0.0 - - - - [70]
Kebili 31 - - 25.8 - - - -
Wild animals
Marié, 2016 2016 Djibouti Djibouti Ruminants 11 - 25.3 - - - - - [66]
Darwish, 1983 1983 Pakistan Karachi Rodents 157 - - - - - - 4.5 [45]
Horses
Marié, 2016 2016 Djibouti Djibouti Equids 10 - 90.0 - - - - - [66]
Pourmahdi, 2013 2011–2012 Iran Khuzestan Province Horse 155 - - 70.3 - - - - [71]
Chinikar, 2013 2010–2012 Iran Total Equine 315 - 2.8 - - - - - [33]
Golestan 65 - 6.1 - - - - -
Gilan 98 - 2.0 - - - - -
Isfahan 152 - 1.9 - - - - -
Ahmadnejad, 2011 2008–2009 Iran 27 provinces of Iran Equine 1054 0.8 - - 23.6 - - - [72]
Abutarbush, 2014 2012 Jordan Irbid, Ajlun and Jerash Horse 253
-
- - 24.9 0 - - [73]
Amman and Madaba
Ma’an, Karak, Tafelah and Aqaba
Mafraq and Zarka
Jordan Valley and Balqa
Benjelloun, 2017 2011 Morocco 4 zones Horse 840 - - 31.0 - - - - [74]
Durand, 2016 2012 Morocco Total Horse 349 - 60.0 - 74.0 - - - [67]
Agadir - 65.0 - - - -
Benslimane - 25.0 - - - -
Casablanca - 75.0 - - - -
Kenitra - 82.0 - - - -
Khenifra - 29.0 - - - -
Marrakech - 32.0 - - - -
Meknes - 34.0 - - - -
Salé - 50.0 - - - -
Sidi Slimane - 100 - - - -
Temara - 94.0 - - - -
Zohaib, 2015 2012–2013 Pakistan Punjab,
Khyber Pakhtunkhwa
Equine 449 - 65·0 - 55·4 - - - [75]
Azmi, 2017 2014 Palestine NA Equids 585 - - 75.0 - - - - [69]
DeCarlo, 2017 NA Qatar Throughout the country Horse 161 - - 27.0 - - - - [76]
Haroun, 2017 2006–2014 Qatar Qatar Horse 260 0 - 23.5 - - - - [77]
Al-Ghamdi, 2014 2007 Saudi Arabia Al-Ahsa Horse 63 - 33.3 - - - - [78]
Bargaoui, 2015 2009 Tunisia Jendouba, Monastir, Chott El Jerid, Chott el Gharsa Equine 1189 - 28.0 - - - - - [79]
Ben Hassine, 2014 2012 Tunisia Kebili Equine 284 - 45.2 - 42.3 - - - [80]
Wernery, 2007 NA UAE Total Equine 750 - - 19.2 - - - - [81]
Al Fujairah - 11.5
Ras Al Khaimah - 5.4
Ajman - 7.1
Sharjah - 8.2
Dubai - 10.0
Al Ain - 12.0
Abu Dhabi - 28.6
Birds
Fereidouni, 2011 2003–2007 Iran Mazandaran, Gilan, West Azerbaijan, Tehran, Fars, Khuzestan 27 species NT+IF = 519;
RT-PCR = 400
- - - 15.0 - 0 [82]
Figuerola, 2009 2008 Morocco Sidi Allal Tazi, Sidi Kacem Wild birds 346 - - - 3.5 - - - [83]
Hammouda, 2015 2012–2015 Tunisia Gabès Wild Sparrow 154 - 0.7 - 0.7 - - -
Kébili oases 54 - 1.9 - 1.9 - - - [84]
Ayadi, 2017 2015 Tunisia Total Laughing doves 226 - - 17.0 10 - - - [85]
Kettana 102 - - 23.0 15 - - -
Gafsa 53 - - 13.0 6.0 - - -
Degache 26 - - 4.0 4.0 - - -
Oum-Errous 45 - - 16.0 7.0 - - -

* 80% of ELISA positive samples were positive by NT.

Abbreviations: SS: Sample Size, ELISA: Enzyme-linked Immunosorbent Assay, cELISA: Competitive ELISA, NT: Neutralization Test, IF: Immunofluorescence Assay, HI: Hemagglutination Inhibition Assay, CF: Complement Fixation, RT-PCR: Reverse Transcriptase-Polymerase Chain Reaction, NA: Data was not available, UAE: United Arab Emirates.

Infection rate of vectors with WNV in the EMRO region

Nine studies investigated arthropods in order to analyze the WNV infection rate among vectors. These reports were from Djibouti (n = 2), Egypt (n = 2), Iran (n = 2), Lebanon (n = 1), Pakistan (n = 1), and Tunisia (n = 1). The primary vector of WNV, i.e., Cx. pipiens s.l. [2], was detected in Djibouti, Egypt, Iran, and Tunisia, and in all theses countries WNV infection in Cx.pipiens s.l. was identified. WNV infection was also detected in a wide range of other vector species, including Cx. quinquefasciatus (Djibouti), Ae. caspius (Iran), Cx. antennatus (Egypt), Cx. perexiguus (Egypt), and Argas reflexus hermannii (Egypt). Details for studies on WNV infection vectors are provided in Table 4 and Fig 3.

Table 4. Summary of studies on the West Nile virus infection rate in vectors of the EMRO region (n = 9).

Author, Pub. year Study year Country City/governorate Species SS Collection Method Pools Test MIR* Ref
(n) (n/1000)
Faulde, 2012 2010–2012 Djibouti Djibouti Cx. quinquefasciatus 19069 CDC-light Traps NA RT-PCR 0.9 [24]
Cx. pipiens s.l. 686 2.9
Faulde, 2010 2008–2009 Djibouti Djibouti Culex spp. 600 CDC- light Traps NA RT-PCR 0 [86]
Turell, 2002§ 1993 Egypt Aswan city
(3 villages:
NagÕ El Hagar, Sabil AbuEl Magd, ElRaghama, NagÕ El Ghuneimiya, El Naghaghra)
Total 36024 NA 32 VI+IF 0.8 [87]
An. multicolor 5 0
An. pharoensis 145 0
An. tenebrosus 245 0
Cx. antennatus 2691 1.9
Cx. perexiguus 9011 2.6
Cx. pipiens s.l. 6982 0.3
Cx. poicilipes 26 0
Ae. caspius 16889 0
Uranotaenia unguiculata 30 0
Sand flies 676 0
Culicoides spp. 200 0
Hard ticks 78 0
Schmidt 1964 1960 Egypt Sheikh Argas reflexus hermanni 1400 NA 28 VI 4.3 [88]
Bagheri, 2015 2015 Iran West Azerbaijan An. maculipennis 368 Dipping 45 RT-PCR 0 [15]
Cx. longiareolata 130 0
Cx. hortensis 1 0
Cx. pipiens s.l. 354 0
Cx. theileri 618 0
Ae. caspius 672 33.3
Shahhosseini, 2017 2015–2016 Iran Gilan, Mazandaran, Golestan, East Azerbaijan, Lorestan Cx. pipiens s.l. 21060 Biogents Sentinel Traps 1222 RT-PCR 0 [14]
Cx. Sitiens 10995 0
Cx. theileri 3856 0
Cx. perexiguus 486 0
Cx. pipiens s.l. 326 3.1
An. hyrcanus 180 0
An. maculipennis s.l. 117 0
An. superpictus 109 0
Cx. tritaeniorhynchus 42 0
An. stephensi 16 0
An. claviger 15 0
Cx. pipiens form pipiens x molestus 15 0
Culiseta longiareolata 15 0
Cx. mimeticus 14 0
Cx. hortensis 11 0
Ae. caspius 8 0
An. pseudopictus 8 0
Cx. pipiens cf. quinquefasciatus 8 0
An. dthali 6 0
An. fluviatilis s.l. 6 0
Cx. pipiens pipiens form molestus 5 0
An. apoci 4 0
An. marteri 4 0
An. plumbeus 4 0
Ae. vexans 2 0
Garabedian, 1971ǂ 1962–1963 Lebanon NA Aedes spp. (mostly) 5131 NA NA VI 0 [18]
Reisen, 1982 1978–1979 Pakistan Punjab Cx. tritaeniorhynchus,
Cx.quinquefasciatus,
Cx. pseudovishnui
44797 Dipping, Biting, Resting outdoors & indoors NA VI 0 [89]
Wasfi, 2016 2014 Tunisia El Felta, Saddaguia Cx. pipiens s.l. 102 CDC-light Traps 21 RT-PCR 68.6 [90]

* MIR was calculated by dividing the number of positive pools by the total number of specimens tested and multiplied by 1000. Where the number of tested specimens is below 1000, the MIR may not accurately represent the true infection rate in the population, and should be interpreted with caution.

§ Mosquitoes were sorted to species, pooled, and processed for virus isolation both by intracerebral inoculation into suckling mice and by inoculation into cell culture. A total of 33 virus isolates was made from 36,024 mosquitoes. Virus identification was performed using indirect fluorescent antibody testing.

ǂ The data for this studiy is driven from articles’ abstract, as their full-text could not be obtained.

Abbreviations: SS: Sample Sizes, MIR: Minimum Infection Rate, NA: Data was not available, RT-PCR: Reverse Transcriptase-Polymerase Chain Reaction, VI: Virus Isolation, IF: ​​Immunofluorescence Assay.

Fig 3. Vector infection with the WNV in the EMRO region.

Fig 3

From each study, only the names of vector species with evidence of WNV infection are written on the map. Countries, from which the main vector for WNV (i.e., Cx. pipiens s.l.) was detected, are colored in orange. These countries include Djibouti, Egypt, Iran, and Tunisia, all of which showed evidence of infection in the vector Cx. pipiens s.l.. Countries with no data on study on vectors are colored in gray. Among countries with available data, only Lebanon had zero infection rates for all studied vector species.

Discussion

Seroprevalence of WNV has been investigated in 14 of 22 countries in the EMRO region. Since 1942, WNV antibodies have been detected in the general population in 11 countries with available data, including: Djibouti, Egypt, Iran, Iraq, Jordan, Lebanon, Libya, Morocco, Pakistan, Sudan, and Tunisia. Our results also suggested that the overall seroprevalence of WNV has been lower in reports from more recent years (since 2010) compared to reports compiled between 1942 and 2009.

Although the presence of WNV infection remains unknown in countries without data in the EMRO region (n = 14), it can be implied that the virus may probably circulate within these countries as well. Existing evidence suggests cross-country dispersion of a number of viruses such as human immunodeficiency virus (HIV) [91] and hepatitis B virus (HBV) [92]. These observations can imply the hypothesis in which WNV also have dispersed across countries in the region, affecting localities (countries) adjacent to infected areas. The argument is further strengthened if we consider the transmission routes of HIV, HBV, and WNV. The transmission of HIV and HBV depends on effective human-to-human contacts, which acts as a barrier for virus dispersion over large geographic distances. However, similar to other arboviruses like Dengue and Crimean-Congo Hemorrhagic Fever [93, 94], the cross-country spread of WNV can be much easier and fast as it can be transmitted through a broad range of vectors and reservoirs.

Most of the seroepidemiological studies included in this review used ELISA for the detection of anti-WNV antibodies. Although this assay is simple, sensitive, and commercially available, it suffers from cross-reactivity with antibodies raised against other flaviviruses. So, using the ELISA method for testing individuals with a history of vaccination against, or infection with related flaviviruses can yield false positive results [95]. To achieve a more specific measurement, positive ELISA test results should be confirmed by the plaque reduction neutralization test (PRNT), which is considered as the gold standard method for WNV serological testing. However, PRNT can detect antibodies at levels that neutralize the virus; therefore, it has low sensitivity for seroepidemiological studies in weakly-exposed populations [95].

Approximately, one-fifth of WNV infected individuals demonstrate symptomatic infection [96]. Clinical symptoms are also non-specific to the disease and include fever, malaise, headache, back pain, myalgia, and anorexia. Therefore, WNV infected individuals can be misdiagnosed with other febrile infections. In areas with evidence of WNV circulation, WNV infection should be considered as a differential diagnosis for patients demonstrating non-differential febrile syndroms.

Non-specific sympotoms of the WNV infection also highlights the need for laboratory testing of suspected human cases. While WNV IgM is the most common target for confirmation of the infection, viral RNA testing can also be performed. Combining IgM detection and viral RNA testing can enhance the possibility of diagnosis in patints with West Nile fever, as indicated by Tilley et al. [97]. However, among 15 studies on patient populations, only four used a combination of serological and molecular assays for the diagnosis of WNV infection.

In this review, we have highlighted serological evidence of WNV infection from 22 independent studies conducted on animal populations in the region. These studies were carried out in 10 countries including, Djibouti, Iran, Jordan, Morocco, Pakistan, Palestine, Qatar, Saudi Arabia, Tunisia, and the UAE. Most studies, have investigated evidence of WNV infection among domestic animals. Since 2010, the highest prevalence of WNV among domestic animals, has been reported among dogs of Morocco and equids of Morocco, Pakistan, Palestine and Iran. The high rates of animal seropositivity and geographic distribution of animal infection reflect the favorable conditions for the circulation of WNV in these countries. In these areas, stronger preventive measures should be considered to reduce the risk of WNV transmission to humans and horses. High seropositivity among dogs and equids also suggests that these animals can be useful sentinels for WNV surveillance, as discussed by previous studies [98100]. Resnick, et al. (2008) reported that WNV seroconversion in dogs happened six weeks prior to the infection in exposed human cases [100].

Only two studies from Pakistan (on rodents) [45] and Djibouti (on wild ruminants) [66]) have investigated wild animals’ infection with WNV. The paucity of published studies on the prevalence of WNV infection in wild animals of the EMRO region underlines a gap in current knowledge about the issue. Knowledge about the reservoirs’ infection and virus circulation among wild animals has important implications for forecasting the emergence or re-emergence of WNV epidemics[95]. So, it is recommended future seroprevalence studies include representative samples from wild animals to further illuminate the state of the infection among these hosts.

Four studies investigated the infection among birds from Iran, Morocco, and Tunisia, from which only two studies were recently performed (i.e., Tunisia, 2015 and 2017). These observations also highlight a gap in current knowledge, this time, on the extend of the infection among birds of the EMRO region. Birds play a critical role in the maintenance and spread of the virus. Prolonged high levels of viremia have been demonstrated in several bird species [101, 102]. The virus has also been isolated from several migratory birds. Thus, surveillance of WNV infection among birds would be of great importance, especially in areas with favorable ecological conditions for birds and mosquitoes. In this regards, a better understanding of birds migration routes would be helpful in selecting the most probable sites for tracking the virus [102], and subsequently making judgments on what areas might be focal points for the emergence of WNV outbreaks.

Mosquitoes and birds are currently considered to have the key role in the life cycle of the virus [2]. However, there are more than 30 other vertebrates such as lemurs, frogs, hamsters, squirrels, rabbits, and chipmunks that have been reported as possible reservoirs for the virus, since they can provide viremia levels that are sufficient to infect mosquito vectors [103]. The role of these reservoirs in the WNV life cycle and epidemic has been less regarded till now, and is an open area for future research.

Despite the critical role of the vector in the life cycle and the epidemic of WNV, only nine studies have investigated vector infection in the region. These studies have been conducted in Djibouti, Egypt, Iran, Pakistan, and Tunisia. The primary vector of WNV, i.e., Cx. pipiens s.l. [2] was detected in all investigared countries except Pakistan. Although WNV infection has been detected in more than 60 mosquito species, detection of viral infection in a mosquito alone does not indicate that the mosquito is a competent vector for the virus. In addition to Culex species, WNV has also been detected in Aedes and Mansonia mosquitoes. Additional studies are necessary to further clarify the potential role these species in the maintenance and transmission of WNV. Interestingly, WNV infection was observed in ticks Argas reflexus hermannii. Previous studies from other regions of WHO also detected WNV RNA in ticks R. turanicus and mites D. gallinae and O. sylvarum. However, their competency as vectors is less clear [104]. Reducing virus transmission from a vector is one of the main strategies of controlling arboviral diseases. Therefore, more efforts to identify the main vectors and understand virus–vector interaction in burdened countries would benefit disease control strategies [105].

The main limitations of this systematic review relate to the data. First, there is a paucity of prevalence studies in the EMRO region, and the quality of data reported by studies varied. For instance, many available studies on human populations were focused on adults, or did not report age and gender for the study sample. The remaining studies included a broad range of age groups (including infant, children, and adults), most of which did not report age and gender specific prevalence. Prevalence data on healthy infants and young children alone was particularly sparse. Therefore, the state of the epidemic among different age and sex groups remains unknown in this region and requires further study with representative samples. Although current data provides a good basis for an overall judgment about the presence of current/past WNV exposure in most investigated samples, they can hardly be used to infer the actual prevalence and state of the epidemic in most investigated countries. For example, only in four countries with available data on the ‘general population’ (i.e., Egypt, Iran, Lebanon, and Pakistan), the total number of tested individuals was reasonably representative of the target population (i.e., more than 1000). These ‘powerful’ studies, however, were not totally flawless. One of the main limitations of these studies was that some of them had used convenience (non-random) sampling methods. In convenience sampling, individuals have unequal and unknown probability of being selected [106]. Hence, the resulting seroprevalence estimates should be generalized to the target population with caution. Few studies available from animal populations in the region also suffered from the abovementioned shortcomings; i.e., non-random sampling and small sample sizes. For example, the seroprevalence of WNV has been investigated in Morocco, Palestine, and Tunisia, but only the study in Morocco has provided the estimate based on a fairly representative sample of 556 and 836 camels for the years 2003 and 2009, respectively. The case was even worse for the seroprevalence studies on dogs, cows, sheep, goats, buffalos, and birds as none of the available studies were well-powered enough (i.e., had small sample sizes). The situation was more satisfactory for the population of horses, where a number of studies with large sample sizes were available from different parts of Iran, Morocco, Pakistan, Palestine, Tunisia, and the UAE. Second, the relative dearth of recent seroprevalence studies, particularly from burdened areas for WNV infection and high-risk population groups is a serious limitation. As the face of WNV disease and its geographic range changes rapidly, WNV prevalence estimated by older studies may not properly reflect the current status of WNV circulation. Less accurate serological tests used by older studies also affect the validity and reliability of the prevalence estimates in these studies. Standardized seroprevalence studies at national levels are critical to best appraise the epidemic status, the impact of interventions and the potentials for future outbreaks. Third, substantial within-country heterogeneity in the prevalence of WNV was noted. This might be due to diversity in the geographical areas, target groups, and the reported sample sizes of studies. Local prevalence estimates, hence, might not be representative of national level prevalence, particularly in large countries with much geographic and ethnic disparities. Finally, our review is limited to reports written in English.

Conclusions

This review provides estimates of the scale of the WNV epidemic at country and regional levels in order to inform efforts for developing and implementing effective future responses. Our results suggested the circulation of WNV in humns, animals, or vectors of most investigated countries in the region. However, there is paucity of data about WNV infection, especially with respect to the burden of the infection in most countries across the region. Hence, further epidemiological studies that take into account the human, reservoir and vector dimension/aspect of the occurrence and distribution of the virus should be conducted particularly in high-prevalent countries. Such research effort will generate robust knowledge and a detailed understanding of the epidemiology of the infection in local populations, and foster in-depth investigations about transmission patterns of the virus. Identification of the geographic distribution of primary reservoirs of the virus and their infection status can also enhance targeted prevention and elimination efforts and aid forecasting attempts. Moreover, surveillance capacities in EMRO countries ought to be established or expanded for better monitoring of WNV infection at national and regional levels.

Supporting information

S1 File. PRISMA 2009 checklist.

(DOC)

S2 File. Search strategy.

(DOCX)

Acknowledgments

The authors would like to thank Dr. Ehsan Mostafavi and Dr. Glory Atilola for the critical review of the manuscript.

Data Availability

All relevant data are within the manuscript.

Funding Statement

The authors received no specific funding for this work.

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Associated Data

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Supplementary Materials

S1 File. PRISMA 2009 checklist.

(DOC)

S2 File. Search strategy.

(DOCX)

Data Availability Statement

All relevant data are within the manuscript.


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