Model-based assessment of Chikungunya and O’nyong-nyong virus circulation in Mali in a serological cross-reactivity context

Abstract

Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-reactivity between Chikungunya (CHIKV) and O’nyong-nyong virus (ONNV) as a case study. We develop a statistical model to assess the epidemiology of these viruses in Mali. We additionally calibrate the model with paired virus neutralization titers in the French West Indies, a region with known CHIKV circulation but no ONNV. In Mali, the model estimate of ONNV and CHIKV prevalence is 30% and 13%, respectively, versus 27% and 2% in non-adjusted estimates. While a CHIKV infection induces an ONNV response in 80% of cases, an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases. Our study shows the importance of conducting serological assays on multiple cross-reactive pathogens to estimate levels of virus circulation.

Seroepidemiological Reconstruction of Long-term Chikungunya Virus Circulation in Burkina Faso and Gabon

“…There are other alphaviruses in Africa. In particular, ONNV has been identified in a number of countries, although not in Burkina Faso or Gabon [ 14 , 25 ]. Most of our CHIKV-seropositive samples from Burkina Faso were also seropositive to ONNV.…”

“…While the higher PRNT titers for ONNV compared to CHIKV seen for many samples suggest that ONNV may have infected at least some of these persons, cross-neutralization titers for these viruses can sometimes be higher than for homologous neutralization [ 26 ], possibly reflecting original antigenic sin. Furthermore, previous modeling exercises have suggested that CHIKV infection induces an ONNV neutralization response in 80% of instances whereas an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases [ 14 ]. Overall, firm conclusions are difficult to reach without information on which of the viruses circulate in a given region.…”

“…However, without systematic surveillance systems that can reliably and consistently capture outbreaks, the long-term epidemiology of CHIKV in the continent remains poorly understood. In addition, distinguishing antibodies resulting from CHIKV infection, as opposed to the close African alphavirus relative o’nyong-nyong virus (ONNV), is technically challenging [ 14 ]. The introduction of CHIKV into the Americas was followed by rapid dispersal throughout the continent, with virtually all countries affected—it remains unknown if such near synchrony in CHIKV epidemiology is present in Africa.…”

Serological Evidence of Exposure to Onyong-Nyong and Chikungunya Viruses in Febrile Patients of Rural Taita-Taveta County and Urban Kibera Informal Settlement in Nairobi, Kenya

“…The results from confirmatory PRNT testing showed that none of the patients had neutralizing antibodies against SINV and that most of the PRNT-positive samples preferentially neutralized ONNV over CHIKV. This may be due to actual ONNV infection or cross-reactivity of CHIKV antibodies with ONNV as has been reported before [37,45]. It could also be due to sequential infection with both viruses in the past.…”

“…Samples were considered as PRNT positive if the PRNT titer was >40, positive for ONNV if ONNV titers were at least two-fold higher than CHIKV titers, and CHIKV positive if CHIKV titers were at least four-fold higher than ONNV titers [5]. The threshold was lower for ONNV than CHIKV because of the unique one-way cross-reactivity between CHIKV and ONNV-CHIKV antibodies are more likely to cross-react with ONNV antigens than ONNV antibodies with CHIKV antigens [37]. The virus strains used were CHIKV LR2006_OPY1 (GenBank EU224268.1), ONNV IbH 12628 and SINV Lovanger strain (GenBank KF737350.1).…”