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.
Example: The severe acute respiratory syndrome (SARS) epidemic originating from China in 2002 was caused by a previously uncharacterized coronavirus that could be identified by specific RT-PCR amplification. Efforts to control future SARS outbreaks depend on the accurate and early identification of SARS-CoV infected patients. A real-time fluorogenic RT-PCR assay based on the 3 -noncoding region (3 -NCR) of SARS-CoV genome was developed as a quantitative SARS diagnostic tool. The ideal amplification efficiency of a sensitive SARS-CoV RT-PCR assay should yield an E value (PCR product concentration increase per amplification cycle) equal to 2.0. It was demonstrated that the 3 -NCR SARS-CoV based RT-PCR reactions could be formulated to reach excellent E values of 1.81, or 91% amplification efficacy. The SARS-CoV cDNA preparations derived from viral RNA extract and the cloned recombinant plasmid both exhibit the identical amplification characteristics, i.e. amplification efficacy using the same PCR formulation developed in this study. The viral genomic copy (or genomic equivalences, GE) per infectious unit (GE/pfu) of SARS-CoV used in this study was also established to be approximate 1200-1600:1. The assay's detection sensitivity could reach 0.005 pfu or 6-8 GE per assay. It was preliminarily demonstrated that the assay could efficiently detect SARS-CoV from clinical specimens of SARS probable and suspected patients identified in Taiwan. The 3 -NCR based SARS-CoV assay demonstrated 100% diagnostic specificity testing samples of patients with acute respiratory disease from a non-SARS epidemic region.
Example solution: Development and evaluation of an efficient 3 -noncoding region-based SARS coronavirus (SARS-CoV) RT-PCR assay for detection of SARS-CoV
Example explanation: It's a correct title because the paragraph described the development of 3 -noncoding region of SARS-CoV genome and assay efficiently detecting SARS-CoV from clinical specimens.

Problem: Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the COVID-19 pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider both the age composition of local and national contexts as well as the social connectedness of older and younger generations. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted nowcasting. Governments are rapidly mobilizing to minimize transmission of COVID-19 through social distancing and travel restrictions to reduce fatalities and the outstripping of healthcare capacity. It is becoming clear that the pandemic's progression and impact may be strongly related to the demographic composition of the population, specifically population age structure. Demographic science can provide new insights into how the pandemic may unfold and the intensity and type of measures needed to slow it down. Currently, COVID-19 mortality risk is highly concentrated at older ages, particularly those aged 80+. In China, case-fatality rate (CFR) estimates range from 0.4% (40-49 years), jumping to 14.8% (80+ years).(1) This is consistent with the data from Italy as of March 16, where the reported CFR is 11.8% for those 70-79, 18.8% for 80-89, and 21.6% for those >90. Thus far in Italy, only 1.5% of deaths have occurred in those under aged 60.(2) As testing becomes more widespread, these case fatality rates may come down due to an increase in the true denominator. Nonetheless, in South Korea where testing was broader and the health system not overtaxed, the current CFR for those 80+ is still an alarming 9.26%. (7) The Importance of Age Structure Population age structure may explain the remarkable variation in fatalities across countries and why countries such as Italy are especially vulnerable. The deluge of critical and fatal COVID-19 cases in Italy was unexpected given the health and wealth of the affected region. Italy is one of the oldest populations in the world with 23.3% its population over age 65, compared to 12% in China (3). Italy is also a country characterized by extensive intergenerational contacts which are supported by a high degree of residential proximity between adult children and their parents (4). Even when inter-generational families do not live together, daily contacts among non-co-resident parent-child pairs are frequent. Many Italians also often prefer to live close to their extended family and commute to work daily.
Solution: Demographic science aids in understanding the spread and fatality rates of COVID-19