A one health approach to the investigation and control of MERS-CoV among camel and human populations in Jordan as a potential model for the region

A stratified multi-stage cross-sectional survey will be conducted among Bedouin communities and their camels in the southern governorates of Jordan (Aqaba & Ma'an) during the period April 2017 to April 2018. These governorates have been selected due to their high number of camel owners, long porous border with Saudi Arabia to the south and already established RVC relationships. Camel owning households and and non-camel owning households will be randomly selected in a 4:1 ratio using local government data of registered livestock owners. Blood samples and oral and nasal swabs will be collected from all family members and a physical examination performed. A pre-tested, structured questionnaire to identify risk factors for MERS-CoV infection will also be administered at this time. Based on an expected prevalence of 4% MERS-CoV seroprevalence among camel owning households and a 0.5% expected seroprevalence among non-camel owners (a risk ratio of 8) a 1:4 ratio of camel herders to non-camel herders and an 80% power, with a 90% confidence interval and a design effect of 1.25 to account for clustering - sample size has been calculated as 946 individuals, with 757 camel herders and 189 non-camel herders. Nasal swabs will also be taken from those camels belonging to selected owners. The number of camels to be randomly sampled per herd has been calculated as 11, using an expected prevalence of 15% and a confidence level of 80% and a mean herd size of 12. In herds of less than 11 camels all camels will be tested. Human serum samples will be screened using anti-MERS coronavirus ELISA (IgG) with microneutralization assay performed as confirmatory test. Human nasal and oral swabs, and camel nasal swabs will be tested by PCR to identify MERS-CoV viral RNA. All samples will be shipped to the US and diagnostics performed at NIAD/NIH Virus Ecology Group, Rocky Mountains Laboratories, Montana. Laboratory and risk factor data will then be subject to multivariate statistical analysis.