Seroepidemiology of Crimean-Congo Haemorrhagic Fever among cattle in Cameroon:Implications from a One Health perspective

BACKGROUND: Crimean-Congo Haemorrhagic Fever (CCHF) is a tick-borne viral zoonotic disease distributed across several continents and recognized as an ongoing health threat. In humans, the infection can progress to a severe disease with high fatality, raising public health concerns due to the limited prophylactic and therapeutic options available. Animal species, clinically unaffected by the virus, serve as viral reservoirs and amplifier hosts, and can be a valuable tool for surveillance. Little is known about the occurrence and prevalence of Crimean-Congo Haemorrhagic Fever Virus (CCHFV) in Cameroon. Knowledge on CCHFV exposure and the factors associated with its presence in sentinel species are a valuable resource to better understand transmission dynamics and assess local risks for zoonotic disease emergence. METHODS AND FINDINGS: We conducted a CCHFV serological survey and risk factor analysis for animal level seropositivity in pastoral and dairy cattle in the North West Region (NWR) and the Vina Division (VD) of the Adamawa Region in Cameroon. Seroprevalence estimates were adjusted for sampling design-effects and test performance. In addition, explanatory multivariable logistic regression mixed-effects models were fit to estimate the effect of animal characteristics, husbandry practices, risk contacts and ecological features on the serological status of pastoral cattle. The overall seroprevalence was 56.0% (95% CI 53.5–58.6) and 6.7% (95% CI 2.6–16.1) among pastoral and dairy cattle, respectively. Animals going on transhumance had twice the odds of being seropositive (OR 2.0, 95% CI 1.1–3.8), indicating that animal movements could be implicated in disease expansion. From an ecological perspective, absolute humidity (OR 0.6, 95% CI 0.4–0.9) and shrub density (OR 2.1, 95% CI 1.4–3.2) were associated with seropositivity, which suggests an underlying viral dynamic connecting vertebrate host and ticks in a complex transmission network. CONCLUSIONS: This study demonstrated high seroprevalence levels of CCHFV antibodies in cattle in Cameroon indicating a potential risk to human populations. However, current understanding of the underlying dynamics of CCHFV locally and the real risk for human populations is incomplete. Further studies designed using a One Health approach are required to improve local knowledge of the disease, host interactions and environmental risk factors. This information is crucial to better project the risks for human populations located in CCHFV-suitable ecological niches

A case-control study to identify risk factors associated with avian influenza subtype H9N2 on commercial poultry farms in Pakistan

A 1:1 matched case-control study was conducted to identify risk factors for avian influenza subtype H9N2 infection on commercial poultry farms in 16 districts of Punjab, and 1 administrative unit of Pakistan. One hundred and thirty-three laboratory confirmed positive case farms were matched on the date of sample submission with 133 negative control farms. The association between a series of farm-level characteristics and the presence or absence of H9N2 was assessed by univariable analysis. Characteristics associated with H9N2 risk that passed the initial screening were included in a multivariable conditional logistic regression model. Manual and automated approaches were used, which produced similar models. Key risk factors from all approaches included selling of eggs/birds directly to live bird retail stalls, being near case/infected farms, a previous history of infectious bursal disease (IBD) on the farm and having cover on the water storage tanks. The findings of current study are in line with results of many other studies conducted in various countries to identify similar risk factors for AI subtype H9N2 infection. Enhancing protective measures and controlling risks identified in this study could reduce spread of AI subtype H9N2 and other AI viruses between poultry farms in Pakistan

Model 2 — Risk factors associated with Avian Influenza type H9N2 infection on commercial poultry farms in Pakistan based on a backward manual stepwise selection process on all variables available in Table 1 except distance to the nearest case farm.

<p>R² = 0.235 (out of possible 0.5)</p><p>^aThe odds of having the distance from the main road <0.5km was 4.59 (CI 95%: 1.09–19.3) times higher than the odds of exposure in the control farms.</p><p>^b*¶Non significant protective factor, i.e odds of having cover on the water storage tank on case farm was 0.313 (CI 95%: 0.068–1.44) times less than the odds of having cover on the water storage tank on control farms.</p><p>^cThe odds of having history of infection with IBD for case was 3.00 (95% CI: 1.44–6.24) times greater than the odds of exposure in the control farm.</p><p>^dThe odds of selling the birds/and or eggs directly to live bird retail shops was 10.6 (CI 95%: 3.37–33.3) times more than the odds of exposure in the control farms.</p><p>Model 2 — Risk factors associated with Avian Influenza type H9N2 infection on commercial poultry farms in Pakistan based on a backward manual stepwise selection process on all variables available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119019#pone.0119019.t001" target="_blank">Table 1</a> except distance to the nearest case farm.</p

Result of univariable analysis by Mantel-Haenszel matched pair analysis of the possible risk factors associated with the risk of AIV H9N2 infection among commercial poultry farms.

<p>*<i>P-value based on Wald statistic</i></p><p>Result of univariable analysis by Mantel-Haenszel matched pair analysis of the possible risk factors associated with the risk of AIV H9N2 infection among commercial poultry farms.</p