TASK DEFINITION: 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.
PROBLEM: Background: Influenza sentinel surveillance in Cote d'Ivoire showed that 70% of Acute Respiratory Infections (ARI) cases remained without etiology. This work aims to describe the epidemiological, clinical, and virological pattern of ARI that tested negative for influenza virus, in children under five years old. Materials and Methods: one thousand and fifty nine samples of patients presenting influenza Like Illness (ILI) or Severe Acute Respiratory Infections (SARI) symptoms were tested for other respiratory viruses using multiplex RT-PCR assays targeting 10 respiratory viruses. Results: The following pathogens were detected as follows, hRV 31,92% (98/307), hRSV 24.4% (75/329), PIV 20.5% (63/307), HCoV 229E 12,05% (37/307), hMPV 6.2% (19/307), HCoVOC43 1.0% (3/307) and EnV 1.0% (3/307). Among the 1,059 specimens analyzed, 917 (86.6%) were ILI samples and 142 (23.4%) were SARI samples. The proportion of children infected with at least one virus was 29.8% (273/917) in ILI cases and 23.9% (34/142) in SARI cases. The most prevalent viruses, responsible for ILI cases were hRV with 35.89% (98/273) and hRSV in SARI cases with 41.2% (14/34) of cases. Among the 1,059 patients, only 22 (2.1%) children presented risk factors related to the severity of influenza virus infection. Conclusion: This study showed that respiratory viruses play an important role in the etiology of ARI in children. For a better understanding of the epidemiology of ARI and improved case management, it would be interesting in this context to expand the surveillance of influenza to other respiratory viruses.

SOLUTION: DETECTION OF NON-INFLUENZA VIRUSES IN ACUTE RESPIRATORY INFECTIONS IN CHILDREN UNDER FIVE-YEAR-OLD IN COTE D'IVOIRE (JANUARY -DECEMBER 2013)

PROBLEM: Human rhinovirus (HRV) infections are common but poorly characterized in university students. Thus, we characterized asymptomatic and symptomatic HRV infections by incidence, species diversity, and viral load of 502 university students during September and October of 2010 and 2011 from nasal swabs and electronically submitted symptom questionnaires. We tested all symptomatic students and randomly sampled participants who remained asymptomatic (n = 25/week, over 8 weeks each study year) on a weekly basis by real-time PCR and sequenced HRV positives. HRV was identified in 33/400 (8.3%) and 85/92 (92.4%) of the asymptomatic and symptomatic students, respectively. We identified a higher than previously reported rate of HRV-B in both groups, although the distribution of HRV species was similar (P = 0.37). Asymptomatic viral load averaged 1.2 log 10 copies/mL lower than symptomatic HRV (P b 0.001). In conclusion, asymptomatic HRV activity preceded peak symptomatic activity in September and October and was associated with lower viral load.

SOLUTION: Comparison of asymptomatic and symptomatic rhinovirus infections in university students: incidence, species diversity, and viral load

PROBLEM: An outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England. We adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China. We predict that a CoVID-19 outbreak will peak 126 to 147 days (~4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate. We provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for health-care capacity planning.

SOLUTION:
A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing