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: The emerging novel human betacoronavirus 2c EMC/2012 (HCoV-EMC) was recently isolated from patients with severe pneumonia and renal failure and was associated with an unexplained high crude fatality rate of 56%. We performed a cell line susceptibility study with 28 cell lines. HCoV-EMC was found to infect the human respiratory tract ( polarized airway epithelium cell line Calu-3, embryonic fibroblast cell line HFL, and lung adenocarcinoma cell line A549), kidney (embryonic kidney cell line HEK), intestinal tract (colorectal adenocarcinoma cell line Caco-2), liver cells (hepatocellular carcinoma cell line Huh-7), and histiocytes (malignant histiocytoma cell line His-1), as evident by detection of high or increasing viral load in culture supernatants, detection of viral nucleoprotein expression by immunostaining, and/or detection of cytopathic effects. Although an infected human neuronal cell line (NT2) and infected monocyte and T lymphocyte cell lines (THP-1, U937, and H9) had increased viral loads, their relatively lower viral production corroborated with absent nucleoprotein expression and cytopathic effects. This range of human tissue tropism is broader than that for all other HCoVs, including SARS coronavirus, HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63, which may explain the high mortality associated with this disease. A recent cell line susceptibility study showed that HCoV-EMC can infect primate, porcine, and bat cells and therefore may jump interspecies barriers. We found that HCoV-EMC can also infect civet lung fibroblast and rabbit kidney cell lines. These findings have important implications for the diagnosis, pathogenesis, and transmission of HCoV-EMC.

SOLUTION: Differential Cell Line Susceptibility to the Emerging Novel Human Betacoronavirus 2c EMC/2012: Implications for Disease Pathogenesis and Clinical Manifestation

PROBLEM: Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the 'convergence model' was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model's predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.

SOLUTION: Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

PROBLEM: With growing amounts of data available, identification of clusters of persons linked to each other by transmission of an infectious disease increasingly relies on automated algorithms. We propose cluster finding to be a two-step process: first, possible transmission clusters are identified using a cluster algorithm, second, the plausibility that the identified clusters represent genuine transmission clusters is evaluated. Aim: To introduce visual tools to assess automatically identified clusters. Methods: We developed tools to visualise: (i) clusters found in dimensions of time, geographical location and genetic data; (ii) nested sub-clusters within identified clusters; (iii) intra-cluster pairwise dissimilarities per dimension; (iv) intra-cluster correlation between dimensions. We applied our tools to notified mumps cases in the Netherlands with available disease onset date (January 2009 -June 2016), geographical information (location of residence), and pathogen sequence data (n = 112). We compared identified clusters to clusters reported by the Netherlands Early Warning Committee (NEWC). Results: We identified five mumps clusters. Three clusters were considered plausible. One was questionable because, in phylogenetic analysis, genetic sequences related to it segregated in two groups. One was implausible with no smaller nested clusters, high intra-cluster dissimilarities on all dimensions, and low intra-cluster correlation between dimensions. The NEWC reports concurred with our findings: the plausible/questionable clusters corresponded to reported outbreaks; the implausible cluster did not. Conclusion: Our tools for assessing automatically identified clusters allow outbreak investigators to rapidly spot plausible transmission clusters for mumps and other human-to-human transmissible diseases. This fast information processing potentially reduces workload.

SOLUTION:
Visual tools to assess the plausibility of algorithm- identified infectious disease clusters: an application to mumps data from the Netherlands