| Literature DB >> 31201040 |
Amy Dighe1, Thibaut Jombart2, Maria D Van Kerkhove3, Neil Ferguson4.
Abstract
Human infection with Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is driven by recurring dromedary-to-human spill-over events, leading decision-makers to consider dromedary vaccination. Dromedary vaccine candidates in the development pipeline are showing hopeful results, but gaps in our understanding of the epidemiology of MERS-CoV in dromedaries must be addressed to design and evaluate potential vaccination strategies. We aim to bring together existing measures of MERS-CoV infection in dromedary camels to assess the distribution of infection, highlighting knowledge gaps and implications for animal vaccination. We systematically reviewed the published literature on MEDLINE, EMBASE and Web of Science that reported seroprevalence and/or prevalence of active MERS-CoV infection in dromedary camels from both cross-sectional and longitudinal studies. 60 studies met our eligibility criteria. Qualitative syntheses determined that MERS-CoV seroprevalence increased with age up to 80-100% in adult dromedaries supporting geographically widespread endemicity of MERS-CoV in dromedaries in both the Arabian Peninsula and countries exporting dromedaries from Africa. The high prevalence of active infection measured in juveniles and at sites where dromedary populations mix should guide further investigation - particularly of dromedary movement - and inform vaccination strategy design and evaluation through mathematical modelling.Entities:
Keywords: Dromedary camels; MERS-CoV; Prevalence of infection; Seroprevalence
Mesh:
Substances:
Year: 2019 PMID: 31201040 PMCID: PMC6899506 DOI: 10.1016/j.epidem.2019.100350
Source DB: PubMed Journal: Epidemics ISSN: 1878-0067 Impact factor: 4.396
Fig. 1Review strategy. Published studies found with all three of our selected search term groups were then assessed against the exclusion criteria resulting in a final selection of 60 publications.
Cross-sectional surveys of MERS-CoV seroprevalence and RNA prevalence in camels.
| Ref | Country | Year | Seroprevalence | RNA prevalence | Stratifications | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| % | na | Rangeb | NTc | % | na | Rangeb | ||||
| ( | Australia | 2013-14 | 0% | 307 | – | 1:10 | – | – | – | – |
| ( | 2014 | 0% | 25 | – | 1:40 | – | – | – | – | |
| ( | Bangladesh | 2015 | 31% | 55 | – | 1:20 | 0% | 55 | – | age, site type, origin, sex, body condition |
| ( | Burkina Faso | 2015 | 80%d | 525 | 73-85% | 1:20 | 5%d | 525 | 0-12% | Region. Further factors assessed in GLMM |
| ( | Canary Islands | 2012-13 | 9% | 105 | – | 1:20 | – | – | – | origin |
| ( | 2015 | 4% | 170 | – | – | – | – | – | origin | |
| ( | Egypt | 1997 | 79% | 43 | – | 1:80 | – | – | – | – |
| ( | 2013 | 92% | 52 | – | 1:20 | 4% | 110 | 3-30% | sex | |
| ( | 2013 | 94% | 110 | – | 1:20 | – | – | – | – | |
| ( | 2014 | 100% | 8 | – | 1:40 | – | – | – | – | |
| ( | 2014-16 | 71% | 2541 | 59-95%e | 1:20 | 15% | 2825 | 1-36%e | origin, site type, sex, month | |
| ( | 2015-16 | 85% | 1031 | 77-96%e | 1:20 | 4% | 1078 | 1-9%e | origin, site type, sex | |
| ( | Ethiopia | 2010-11 | 96%d | 188 | 95-100% | • | – | – | – | region |
| ( | 2013 | 96% | 66 | – | NA | – | – | – | – | |
| ( | 2015 | 96%d | 632 | 85-99% | 1:20 | 10%d | 632 | 0-16% | Region. Further factors assessed in GLMM | |
| ( | Iraq | 2014-15 | 85% | 180 | 85-86% | – | – | – | – | age, region, sex |
| ( | 2015-16 | – | – | – | – | 15% | 100 | 0-35% | age, region, month | |
| ( | Israel | 2012-17 | 62% | 411 | – | 1:20 | 0% | 540 | – | – |
| ( | 2013 | 72% | 71 | – | 1:20 | – | – | – | sex | |
| ( | Japan | <2015 | 0% | 5 | – | 1:20 | 0% | 4 | – | – |
| ( | Jordan | 2013 | 100% | 11 | – | 1:20 | – | – | – | |
| ( | 2016 | 82%d | 45 | 77-87% | – | 62% | 45 | 48-77% | age, region, lifestyle | |
| ( | Kazakhstan | 2015 | 0% | 455 | – | 1:20 | – | – | – | – |
| ( | Kenya | 1992-2013 | 30%f | 228 | 0-100% | – | – | – | – | region, year |
| ( | 2013 | 47%d | 335 | 14-83% | – | – | – | – | age, herd, lifestyle, isolation | |
| ( | 2013 | 90% | NA | – | – | – | – | – | age, region, sex | |
| ( | 2016-17 | – | – | – | – | 0.35%d | 1421 | 0-1.2%d | region, | |
| ( | 2016-18 | 68% | 1163 | 17-87% | 1:20 | 0.95%d | 1163 | – | age, region, sex | |
| ( | KSAk | 1992-2010 | 87%d | 264 | 77-100% | – | – | – | – | age, region, year |
| ( | 2013 | 74% | 150 | 66-100% | – | 25% | 202 | 0-66% | age, region | |
| ( | 2015-16 | – | – | – | – | 14% | 44 | 0-23% | yearg | |
| ( | 2016 | 84% | 171 | – | – | – | – | – | age, sex | |
| ( | 1993 | 90% | 131 | 73-96% | 1:40 | – | – | – | region | |
| ( | 2012-13 | 90% | 310 | 85-94% | 1:20 | – | – | – | age, region | |
| ( | 2015-17 | – | – | – | – | 56% | 698 | 5-85% | region, site-type, month, year | |
| ( | 2013-14 | – | – | – | – | 29% | 96 | – | age, site, month | |
| ( | 2014-15 | – | – | – | – | 0.12% | 1309 | – | – | |
| ( | Mali | 2009-10 | 88% | 562 | 0-91% | • | – | – | – | region |
| ( | Morocco | 2015 | 77%d | 343 | 48-100% | 1:20 | 2%d | 343 | 0-8% | region. Further factors assessed in GLMM |
| ( | Nigeria | 2015 | 96% | 131 | – | 1:20 | 11% | 132 | – | – |
| ( | 2010-11 | 94% | 358 | 82-96% | • | – | – | – | region | |
| ( | 2016 | – | – | – | – | 3%d | 2529 | 0-8.4%h | age, week tested | |
| ( | Oman | 2013 | – | – | – | – | 7% | 76 | – | – |
| ( | 2013 | 100% | 50 | – | 1:20 | – | – | – | – | |
| ( | Pakistan | 2012-15 | 40% | 565 | 0-83% | 1:80 | – | – | – | region |
| ( | 2015-18 | 76% | 1050 | 72-80% | • | 3%d | 776 | – | age, region, sex, lifestyle | |
| ( | Qatar | 2014 | – | – | – | – | 79% | 53 | 67-92% | – |
| ( | 2014 | 100% | 33 | – | 1:** | 21%d | 33 | 0-58% | region | |
| ( | 2014 | – | – | – | – | 2% | 53 | – | – | |
| ( | Somalia | 1983-4 | 81%d | 86 | – | 1:80 | – | – | – | year |
| ( | Sudan | 1984 | 82% | 60 | – | 1:80 | – | – | – | year |
| ( | Tunisia | 2009 | 49%d | 204 | 36-100% | • | – | – | – | region |
| ( | UAEl | 2003 & 13 | 97% | 651 | – | • | – | – | – | year |
| ( | 2005 | 82% | 11 | 0-100%e | 1:12 | – | – | – | site | |
| ( | 2014 | 93% | 853 | – | – | 5% | 871 | – | age | |
| ( | <2015 | 95% | 254 | – | – | 0% | 254 | – | age | |
| ( | 2014 | – | – | – | – | 1.6% | 7803 | – | site-type | |
| ( | 2015 | – | – | – | – | 29%i | 376i | – | – | |
| ( | USAm & Canada | 2000-1 | 0% | 6 | – | 1:12 | – | – | – | – |
| ( | UAE | 2012 | – | – | – | – | 4% | 1113 | farm | |
| ( | UAE | 2014 | – | – | – | – | 100% j | 6j | – | – |
| ( | UAE | 2015 | 100% | 8 | – | 1:40 | 100% | 8 | – | – |
| ( | KSA | 2014-16 | 71% | 595 | 37-100% | • | 13% | 584 | 0-56% | region, age, sex |
| ( | Qatar | 2013 | 100% | 14 | – | 1:20 | 21% | 14 | – | – |
| ( | Qatar | 2014 | 97% | 103 | – | • | 59% | 105 | – | – |
| ( | Mongolia | 2014 | 0% | 190 | – | 1:2 | 0% | 190 | – | |
| ( | Mongolia | 2015 | 0% | 200 | – | 1:2 | 0% | 200 | – | |
| ( | Kazakhstan | 2015 | 0% | 95 | – | – | – | – | – | |
a. total number of camels sampled.
b. range across sub-national locations surveyed.
c. cut off titre to determine positivity if neutralisation test used.
d. we calculated this value from disaggregated values presented by the authors.
e. range given is across site types rather than geographical locations.
f. neutralisation at dilution >1:80 gave 15% seropositivity but regional range only available for ELISA (Enzyme Linked Immunosorbent Assay) results – reported accordingly.
g. study also tested different site-types but measured RNA in serum sample rather than nasal swab so this was not included.
h. range is across weeks rather than regions.
i. both (Li et al., 2017) and (Yusof et al., 2017) report RNA prevalence from the same study.
j. unclear whether study found negative camels – it only mentions that 6 camels were tested, found positive and viral genomes were isolated.
k. Kingdom of Saudi Arabia.
l. United Arab Emirates.
m. United States of America.
•neutralisation test limited to a subset of samples or only used to detect presence of high titres.
** No positivity cut-off titre given but all samples had incredibly high titres, and were able to neutralise at dilution >1:1280.
Fig. 2Map of MERS-CoV seroprevalence in dromedaries. Measures of MERS-CoV seroprevalence in dromedaries, aggregated at the country level. Total sample size tested is given in parenthesis. Camel density is calculated using FAOSTAT country-level camel population data (FAO, 2016) and World Bank data on country surface area (World Bank, 2016) *value calculated by us from disaggregated sub-national measures of seroprevalence. Red text highlights studies conducted in dromedary populations in response to an epidemiologically linked human MERS-CoV infection. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Studies reporting seroprevalence stratified by age of dromedary.
| Country | Stratified seroprevalence | Reported trend | Reported significance | Ref. |
|---|---|---|---|---|
| Bangladesh | <2yrs | Higher in camels >2yrs | Not significant | ( |
| Burkina Faso, Ethiopia and | Generalised Linear Mixed Model (n = 1500) | Increase with age | ( | |
| Egypt | <2yrs | Higher in camels >2yrs | ( | |
| Ethiopia | 1- ≤2yrs | None | Not significant | ( |
| Iraq | <2yrs | Lower in camels 2-4yrs compared with <2yrs | Not significant | ( |
| Jordan | ≤2yrs | ELISA ratio higher in camels >3yrs | Significant p = NA | ( |
| Kenya | <2yrs | Higher in camels >2yrs than <6 m | ( | |
| Kenya | 1-4yrs | Higher in camels >4yrs | ( | |
| Kenya | <4yrs | Higher in camels >7yrs | ( | |
| KSA | ≤2yrs | Higher in camels >2yrs | ( | |
| KSA | ≤2yrs | Higher in older animals | Not presented | ( |
| KSA | 1-2yrs | Lower in camels >2yrs | ( | |
| KSA | <1 yr | Higher in camels >1 yr | ( | |
| Mali | <2yrs | None | Not significant | ( |
| Pakistan | ≤3yrs | Lower in animals ≤3yrs | ( | |
| Pakistan | ≤2yrs | Higher in older animals | ( | |
| UAE | <1 yr | Lower in calves <1 yr | ( | |
| UAE | <1 yrs | Increase with age | Not tested | ( |
| KSA | ||||
The bold type highlights the aggregated seroprevalence values presented graphically in figure 3.
Age stratified results were calculated by us, using disaggregated results presented by authors.
Number of animals in each age class not supplied.
n = the total number of dromedaries sampled.
Seroprevalence in >2yrs estimated under the assumption that age classes 3-8yrs and 9-16yrs are the same size.
Fig. 3Age stratified seroprevalence. Measures grouped by available stratification and arranged in order of increasing adult seroprevalence. Bars indicate 95% confidence intervals, calculated by us when not stated in the study, if age class size was available (not available for the population in Mali). *indicates that calves <1-year-old were not included. **indicates that the study was conducted in dromedary populations in response to an epidemiologically linked human MERS-CoV infection.
Fig. 4Map of prevalence of active MERS-CoV infection in dromedaries. Measures of MERS-CoV RNA prevalence in dromedaries, aggregated at the country level. Total sample size tested is given in parenthesis. Camel density is calculated using FAOSTAT country-level camel population data (FAO, 2016) and World Bank data (World Bank, 2016) on country surface area. *value calculated by us from disaggregated sub-national measures of RNA prevalence. Red text highlights studies conducted in dromedary populations in response to an epidemiologically linked human MERS-CoV infection. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)