In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Background: Rift Valley fever (RVF) is endemic to the tropical regions of eastern and southern Africa. The seroprevalence of RVF was investigated among the human population in Borno State, Nigeria to determine the occurrence of the disease in the study area in comparison with that of Lassa fever and Crimean-Congo Hemorrhagic fever. Methods: Recombinant nucleoprotein (rNP)-based IgG-ELISAs for the detection of serum antibodies against RVF virus (RVFV), Lassa fever virus (LASV), and Crimean-Congo hemorrhagic fever virus (CCHFV) were used to test human sera in Borno State, Nigeria. The presence of neutralizing antibody against the RVFV-glycoprotein-bearing vesicular stomatitis virus pseudotype (RVFVpv) was also determined in the human sera. Of the 297 serum samples tested, 42 (14.1%) were positive for the presence of RVFV-IgG and 22 (7.4%) and 7 (2.4%) of the serum samples were positive for antibodies against LASV and CCHFV, respectively. There was a positive correlation between the titers of neutralizing antibodies obtained using RVFVpv and those obtained using the conventional neutralization assay with the attenuated RVFV-MP12 strain. Conclusions: The seroprevalence of RVF was significantly higher than that of LASV and CCHF in Borno State, Nigeria. The RVFVpv-based neutralization assay developed in this study has the potential to replace the traditional assays based on live viruses for the diagnosis and seroepidemiological studies of RVF.
Development and validation of serological assays for viral hemorrhagic fevers and determination of the prevalence of Rift Valley fever in Borno State, Nigeria

To combat the threat of many emerging infectious diseases, DNA immunization offers a unique and powerful approach to the production of high-quality monoclonal antibodies (mAbs) against various pathogens. Compared with traditional protein-based immunization approaches, DNA immunization is efficient for testing novel immunogen designs, does not require the production or purification of proteins from a pathogen or the use of recombinant protein technology and is effective at generating mAbs against conformation-sensitive targets. Although significant progress in the use of DNA immunization to generate mAbs has been made over the last two decades, the literature does not contain an updated summary of this experience. The current review provides a comprehensive analysis of the literature, including our own work, describing the use of DNA immunization to produce highly functional mAbs, in particular, those against emerging infectious diseases. Critical factors such as immunogen design, delivery approach, immunization schedule, use of immune modulators and the role of final boost immunization are discussed in detail.
DNA immunization as a technology platform for monoclonal antibody induction

The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID-19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing models. In this paper, a novel stochastic model is proposed which aims to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We find that, (1) instead of aberration, there is a remarkable amount of asymptomatic individuals, (2) an individual with symptoms is approximately twice more likely to pass the disease to others than that of an asymptomatic patient, (3) the transmission rate has reduced significantly since the implementation of control 1 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint .
Prediction of the COVID-19 outbreak based on a realistic stochastic model