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.

Influenza has been well documented to significantly contribute to winter increase of mortality in the temperate countries, but its severity in the subtropics and tropics was not recognized until recently and geographical variations of disease burden in these regions remain poorly understood. In this study, we applied a standardized modeling strategy to the mortality and virology data from three Asian cities: subtropical Guangzhou and Hong Kong, and tropical Singapore, to estimate the disease burden of influenza in these cities. We found that influenza was associated with 10.6, 13.4 and 8.3 deaths per 100,000 population in Guangzhou, Hong Kong and Singapore, respectively. The annual rates of excess deaths in the elders were estimated highest in Guangzhou and lowest in Singapore. The excess death rate attributable to A/H1N1 subtype was found slightly higher than the rates attributable to A/H3N2 during the study period of 2004-2006 based on the data from Hong Kong and Guangzhou. Our study revealed a geographical variation in the disease burden of influenza in these subtropical and tropical cities. These results highlight a need to explore the determinants for severity of seasonal influenza.
Influenza associated mortality in the subtropics and tropics: Results from three Asian cities

Background: Human adenoviruses are common causes of community-acquired respiratory tract and enteric infections. Severe disseminated infections with high mortality rates may be seen in immunocompromised individuals. An accurate and cost-effective quantitative assay is essential not only for laboratory diagnosis of adenoviral infections, but also for monitoring of response to antiviral treatment. The diagnostic performance of an in-house quantitative polymerase chain reaction assay was compared to a commercial system. Methods: The analytical sensitivity, specificity, linearity, precision and accuracy of an in-house adenovirus quantitative polymerase chain reaction assay were evaluated against the RealStar® Adenovirus PCR Kit (Altona Diagnostics GmbH, Hamburg, Germany), using 122 clinical specimens and 18 proficiency testing samples. Results: Linear regression analysis of the quantitative results by the in-house assay showed the dynamic range from 2.60 to 9 log 10 (plasma) and 2.94 to 9 log 10 (viral transport medium) copies/mL, with the coefficient of determination (R 2 ) of 0.996 and 0.998, respectively. A dilution series demonstrated the limits of detection and lower limits of quantification for plasma were 2.06 log 10 and 2.60 log 10 copies/mL and those for viral transport medium were 2.31 log 10 and 2.94 log 10 copies/mL respectively. The precision of the in-house assay was highly reproducible among runs with coefficients of variance ranging from 0.07 to 3.21% for plasma and 0.17% to 2.11% for viral transport medium. A comparison of 52 matched samples showed an excellent correlation between the quantitative viral loads measured by the in-house assay and the RealStar® Adenovirus PCR Kit (R 2 = 0.984), with an average bias of − 0.16 log 10 copies/mL. Conclusions: The in-house adenovirus assay is a sensitive and reliable assay with lower cost for the detection and quantification of adenoviral DNA when compared to the RealStar® Adenovirus PCR Kit.
Comparative evaluation of a laboratory- developed real-time PCR assay and RealStar® Adenovirus PCR Kit for quantitative detection of human adenovirus

The World Health Organization (WHO) has declared the 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model based on machine learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that many FDA approved drugs are potentially highly potent to 2019-nCoV.

Potentially highly potent drugs for 2019-nCoV