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: medRxiv preprint Interpretation Parameters that successfully reproduce the observed number of cases indicate that both R 0 and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis. 1 Balcan D, Gonçalves B, Hu H, Ramasco JJ, Colizza V, Vespignani A. Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model. J Comput Sci 2010; 1 : 132-45. 2 Van den Broeck W, Gioannini C, Gonçalves B, Quaggiotto M, Colizza V, Vespignani A. The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infect Dis 2011; 11 : 37. 3 Tizzoni M, Bajardi P, Poletto C, et al. Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm. BMC Med 2012;

SOLUTION: From a single host to global spread. The global mobility based modelling of the COVID-19 pandemic implies higher infection and lower detection rates than current estimates

PROBLEM: The objectives were to determine the median infective dose (ID 50 ) of Cryptosporidium parvum and to describe the dose-response relationship including associated clinical illness in experimentally challenged dairy calves. Within the first 24 h of life, 27 test calves were experimentally challenged with C. parvum oocysts and 3 control calves were sham dosed. Test calves received 1 of 8 possible doses (25, 50, 100, 500, 1 × 10 3 , 1 × 10 4 , 1 × 10 5 , and 1 × 10 6 oocysts). All 27 test calves developed diarrhea. Fecal oocyst shedding occurred in 25 (92.6%) test calves and in 0 control calves. The 2 non-shedding test calves both received 25 oocysts. There was an inverse relationship between dose and time to onset of fecal oocyst shedding (P = 0.005). There was no relationship found between dose and duration (P = 0.2) or cessation (P = 0.3) of fecal oocyst shedding. In addition, there was not a significant relationship between log-dose and the log-peak oocysts (P = 0.2) or log-total oocysts (P = 0.5) counted/g of feces across the dose groups. There was a positive dose-response relationship between log-dose and diarrhea (P = 0.01). However, when controlling for other factors, such as onset and cessation of fecal oocyst shedding, dose was not a significant predictor of diarrhea (P = 0.5). Onset and cessation of fecal oocyst shedding were found to be the best predictors of diarrhea (P = 0.0006 and P = 0.04, respectively). The ID 50 for fecal oocyst shedding was 5.8 oocysts, for diarrhea was 9.7 oocysts, and for fecal oocyst shedding with diarrhea was 16.6 oocysts. Given that the ID 50 of C. parvum is far less than would be excreted into the environment by a naturally infected calf, prevention and control of cryptosporidiosis is a formidable challenge.

SOLUTION: Cryptosporidium parvum: Determination of ID 50 and the dose-response relationship in experimentally challenged dairy calves

PROBLEM: Annotation of the genome sequence of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus) is indispensable to understand its evolution and pathogenesis. We have performed a full annotation of the SARS-CoV genome sequences by using annotation programs publicly available or developed by ourselves. Totally, 21 open reading frames (ORFs) of genes or putative uncharacterized proteins (PUPs) were predicted. Seven PUPs had not been reported previously, and two of them were predicted to contain transmembrane regions. Eight ORFs partially overlapped with or embedded into those of known genes, revealing that the SARS-CoV genome is a small and compact one with overlapped coding regions. The most striking discovery is that an ORF locates on the minus strand. We have also annotated non-coding regions and identified the transcription regulating sequences (TRS) in the intergenic regions. The analysis of TRS supports the minus strand extending transcription mechanism of coronavirus. The SNP analysis of different isolates reveals that mutations of the sequences do not affect the prediction results of ORFs.

SOLUTION:
Genome Organization of the SARS-CoV