Epidemiology and infection
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Notified cases of dengue infections in Singapore reached historical highs in 2004 (9459 cases) and 2005 (13,817 cases) and the reason for such an increase is still to be established. We apply a mathematical model for dengue infection that takes into account the seasonal variation in incidence, characteristic of dengue fever, and which mimics the 2004-2005 epidemics in Singapore. ⋯ Since the control of immature forms allows the reduction of adulticide, it seems that the best strategy is to combine both adulticide and larvicide control measures during an outbreak, followed by the maintenance of larvicide methods after the epidemic has subsided. In addition, the model showed that the mixed strategy of adulticide and larvicide methods introduced by the government seems to be very effective in reducing the number of cases in the first weeks after the start of control.
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Improving the efficiency of outbreak investigation in restaurants is critical to reducing outbreak-associated illness and improving prevention strategies. Because clinical characteristics of outbreaks are usually available before results of laboratory testing, we examined their use for determining contributing factors in outbreaks caused by restaurants. All confirmed foodborne outbreaks reported to the Centers for Disease Control and Prevention (CDC) from 1982 to 1997 were reviewed. ⋯ Poor personal hygiene was associated with norovirus, Shigella, and Salmonella, and also with outbreaks that fitted norovirus-like and vomiting-toxin clinical profiles. Contributing factors were similar for outbreaks with known aetiology and for those where aetiology was assigned by corresponding clinical profile. Rapidly categorizing outbreaks by clinical profile, before results of laboratory testing are available, can help identification of factors which contributed to the occurrence of the outbreak and will promote timely and efficient outbreak investigations.
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Ebola is a highly lethal virus, which has caused at least 14 confirmed outbreaks in Africa between 1976 and 2006. Using data from two epidemics [in Democratic Republic of Congo (DRC) in 1995 and in Uganda in 2000], we built a mathematical model for the spread of Ebola haemorrhagic fever epidemics taking into account transmission in different epidemiological settings. ⋯ A key parameter was the rapid institution of control measures. For both epidemic profiles identified, increasing hospitalization rate reduced the predicted epidemic size.