In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Paragraph: A substantial proportion of hitherto unexplained respiratory tract illnesses is associated with human metapneumovirus (hMPV) infection. This virus also was found in patients with severe acute respiratory syndrome (SARS). To determine the dynamics and associated lesions of hMPV infection, six cynomolgus macaques (Macaca fascicularis) were inoculated with hMPV and examined by pathological and virological assays. They were euthanized at 5 (n 2) or 9 (n 2) days post-infection (dpi), or monitored until 14 dpi (n 2). Viral excretion peaked at 4 dpi and decreased to zero by 10 dpi. Viral replication was restricted to the respiratory tract and associated with minimal to mild, multi-focal erosive and inflammatory changes in conducting airways, and increased numbers of macrophages in alveoli. Viral expression was seen mainly at the apical surface of ciliated epithelial cells throughout the respiratory tract, and less frequently in type 1 pneumocytes and alveolar macrophages. Both cell tropism and respiratory lesions were distinct from those of SARS-associated coronavirus infection, excluding hMPV as the primary cause of SARS. This study demonstrates that hMPV is a respiratory pathogen and indicates that viral replication is short-lived, polarized to the apical surface, and occurs primarily in ciliated respiratory epithelial cells.
Title: Short Communication Experimental Human Metapneumovirus Infection of Cynomolgus Macaques (Macaca fascicularis) Results in Virus Replication in Ciliated Epithelial Cells and Pneumocytes with Associated Lesions throughout the Respiratory Tract
True

Paragraph: The avian influenza virus H5N1 and the 2009 swine flu H1N1 are potentially serious pandemic threats to human health, and air travel readily facilitates the spread of infectious diseases. However, past studies have not yet incorporated the effects of air travel on the transmission of influenza in the construction of mathematical epidemic models. Therefore, this paper focused on the human-to-human transmission of influenza, and investigated the effects of air travel activities on an influenza pandemic in a small-world network. These activities of air travel include passengers' consolidation, conveyance and distribution in airports and flights. Dynamic transmission models were developed to assess the expected burdens of the pandemic, with and without control measures. This study also investigated how the small-world properties of an air transportation network facilitate the spread of influenza around the globe. The results show that, as soon as the influenza is spread to the top 50 global airports, the transmission is greatly accelerated. Under the constraint of limited resources, a strategy that first applies control measures to the top 50 airports after day 13 and then soon afterwards to all other airports may result in remarkable containment effectiveness. As the infectiousness of the disease increases, it will expand the scale of the pandemic, and move the start time of the pandemic ahead.
Title: Transmission and control of an emerging influenza pandemic in a small-world airline network
False

Paragraph: Although the rapidly rising transmission trend of COVID-19 in Wuhan has been controlled in late February 2020, the outbreak still caused a global pandemic afterward. Understanding Wuhan's COVID-19 transmission dynamics and the effects of prevention approaches is of significant importance for containing virus global transmission. However, most of the recent studies focused on the early outbreaks without considering improvements in diagnostic capability and effects of prevention measures together, thus the estimated results may only reflect the facts in a given period of time. We constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, embedding with latent periods under different prevention measures and proportions of documented infections to characterize the Wuhan COVID-19 transmission cross different stages of the outbreak. The epidemiological parameters were estimated using a particle filtering approach. Our model successfully reproduced the dynamics of the Wuhan local epidemic with two peaks on February 4 and February 12 separately. Prevention measures determined the time of reaching the first peak and caused an 87% drop in the R t from 3.09 (95% CI, 2.10 to 3.63) to 0.41 (95% CI, 0.18 to 0.66). An improved diagnostic capability created the second peak and increased the number of documented infections. The proportion of documented infections changed from 23% (95% CI, 20% to 26%) to 37% (95% CI, 33% to 41%) when the detection kits were released after January 26, and later up to 73% (95% CI, 64% to 80%) after the diagnostic criteria were improved.
Title: The impacts of diagnostic capability and prevention measures on transmission dynamics of COVID-19 in Wuhan
False