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      Quantifying the success of measles vaccination campaigns in the Rohingya refugee camps

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          Abstract

          In the wake of the Rohingya population’s mass migration from Myanmar, one of the world’s largest refugee settlements was constructed in Cox’s Bazar, Bangladesh to accommodate nearly 900,000 new refugees. Refugee populations are particularly vulnerable to infectious disease outbreaks due to many population and environmental factors. A large measles outbreak, with over 1700 cases, occurred among the Rohingya population between September and November 2017. Here, we estimate key epidemiological parameters and use a dynamic mathematical model of measles transmission to evaluate the effectiveness of the reactive vaccination campaigns in the refugee camps. We also estimate the potential for subsequent outbreaks under different vaccination coverage scenarios. Our modeling results highlight the success of the vaccination campaigns in rapidly curbing transmission and emphasize the public health importance of maintaining high levels of vaccination in this population, where high birth rates and historically low vaccination coverage rates create suitable conditions for future measles outbreaks.

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          Most cited references31

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          Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures

          Abstract Severe acute respiratory syndrome (SARS) has been the first severe contagious disease to emerge in the 21st century. The available epidemic curves for SARS show marked differences between the affected regions with respect to the total number of cases and epidemic duration, even for those regions in which outbreaks started almost simultaneously and similar control measures were implemented at the same time. The authors developed a likelihood-based estimation procedure that infers the temporal pattern of effective reproduction numbers from an observed epidemic curve. Precise estimates for the effective reproduction numbers were obtained by applying this estimation procedure to available data for SARS outbreaks that occurred in Hong Kong, Vietnam, Singapore, and Canada in 2003. The effective reproduction numbers revealed that epidemics in the various affected regions were characterized by markedly similar disease transmission potentials and similar levels of effectiveness of control measures. In controlling SARS outbreaks, timely alerts have been essential: Delaying the institution of control measures by 1 week would have nearly tripled the epidemic size and would have increased the expected epidemic duration by 4 weeks.
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            The basic reproduction number (R 0 ) of measles: a systematic review

            The basic reproduction number, R nought (R0), is defined as the average number of secondary cases of an infectious disease arising from a typical case in a totally susceptible population, and can be estimated in populations if pre-existing immunity can be accounted for in the calculation. R0 determines the herd immunity threshold and therefore the immunisation coverage required to achieve elimination of an infectious disease. As R0 increases, higher immunisation coverage is required to achieve herd immunity. In July, 2010, a panel of experts convened by WHO concluded that measles can and should be eradicated. Despite the existence of an effective vaccine, regions have had varying success in measles control, in part because measles is one of the most contagious infections. For measles, R0 is often cited to be 12-18, which means that each person with measles would, on average, infect 12-18 other people in a totally susceptible population. We did a systematic review to find studies reporting rigorous estimates and determinants of measles R0. Studies were included if they were a primary source of R0, addressed pre-existing immunity, and accounted for pre-existing immunity in their calculation of R0. A search of key databases was done in January, 2015, and repeated in November, 2016, and yielded 10 883 unique citations. After screening for relevancy and quality, 18 studies met inclusion criteria, providing 58 R0 estimates. We calculated median measles R0 values stratified by key covariates. We found that R0 estimates vary more than the often cited range of 12-18. Our results highlight the importance of countries calculating R0 using locally derived data or, if this is not possible, using parameter estimates from similar settings. Additional data and agreed review methods are needed to strengthen the evidence base for measles elimination modelling.
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              Estimation of the reproductive number and the serial interval in early phase of the 2009 influenza A/H1N1 pandemic in the USA

              Background  The United States was the second country to have a major outbreak of novel influenza A/H1N1 in what has become a new pandemic. Appropriate public health responses to this pandemic depend in part on early estimates of key epidemiological parameters of the virus in defined populations. Methods  We use a likelihood‐based method to estimate the basic reproductive number (R 0) and serial interval using individual level U.S. data from the Centers for Disease Control and Prevention (CDC). We adjust for missing dates of illness and changes in case ascertainment. Using prior estimates for the serial interval we also estimate the reproductive number only. Results  Using the raw CDC data, we estimate the reproductive number to be between 2·2 and 2·3 and the mean of the serial interval (μ) between 2·5 and 2·6 days. After adjustment for increased case ascertainment our estimates change to 1·7 to 1·8 for R 0 and 2·2 to 2·3 days for μ. In a sensitivity analysis making use of previous estimates of the mean of the serial interval, both for this epidemic (μ = 1·91 days) and for seasonal influenza (μ = 3·6 days), we estimate the reproductive number at 1·5 to 3·1. Conclusions  With adjustments for data imperfections we obtain useful estimates of key epidemiological parameters for the current influenza H1N1 outbreak in the United States. Estimates that adjust for suspected increases in reporting suggest that substantial reductions in the spread of this epidemic may be achievable with aggressive control measures, while sensitivity analyses suggest the possibility that even such measures would have limited effect in reducing total attack rates.
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                Author and article information

                Journal
                101484711
                36817
                Epidemics
                Epidemics
                Epidemics
                1755-4365
                1878-0067
                22 March 2020
                09 January 2020
                09 July 2021
                : 30
                : 100385
                Affiliations
                [a ]Department of Population Health Sciences, Harvard Graduate School of Arts and Sciences, Cambridge, MA USA
                [b ]Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
                [c ]Department of Demography, University of California, Berkeley, Berkeley, CA, USA
                Author notes

                Author contributions

                TC performed the data analyses and drafted the manuscript. COB and ASM designed the research. All authors revised the manuscript and approved the final version.

                [* ]Corresponding author. mahmuda@ 123456berkeley.edu (A.S. Mahmud).
                Article
                NIHMS1578444
                10.1016/j.epidem.2020.100385
                7343595
                31951876
                81674011-7fc5-45ed-9d92-c28c11458c39

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/BY-NC-ND/4.0/).

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                Categories
                Article

                Public health
                measles,vaccination,mathematical modeling,rohingya,bangladesh
                Public health
                measles, vaccination, mathematical modeling, rohingya, bangladesh

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