Pandemics and epidemics have ravaged human societies throughout history. The plague, cholera, and smallpox killed tens of millions of people and destroyed civilizations. In the past 100 years, the “Spanish Flu” of 1918-1919 and HIV-AIDS caused the deaths of nearly 100 million people. Advances in medicine have transformed our defenses against the threat of infectious disease. Better hygiene, antibiotics, diagnostics, and vaccines have given us far more effective tools for preventing and responding to outbreaks. Yet the severe acute respiratory syndrome (SARS), the Middle East respiratory syndrome (MERS), and the recent West African Ebola outbreak show that we cannot be . . .
Yersinia pestis, the etiologic agent of the disease plague, has been implicated in three historical pandemics. These include the third pandemic of the 19(th) and 20(th) centuries, during which plague was spread around the world, and the second pandemic of the 14(th)-17(th) centuries, which included the infamous epidemic known as the Black Death. Previous studies have confirmed that Y. pestis caused these two more recent pandemics. However, a highly spirited debate still continues as to whether Y. pestis caused the so-called Justinianic Plague of the 6(th)-8(th) centuries AD. By analyzing ancient DNA in two independent ancient DNA laboratories, we confirmed unambiguously the presence of Y. pestis DNA in human skeletal remains from an Early Medieval cemetery. In addition, we narrowed the phylogenetic position of the responsible strain down to major branch 0 on the Y. pestis phylogeny, specifically between nodes N03 and N05. Our findings confirm that Y. pestis was responsible for the Justinianic Plague, which should end the controversy regarding the etiology of this pandemic. The first genotype of a Y. pestis strain that caused the Late Antique plague provides important information about the history of the plague bacillus and suggests that the first pandemic also originated in Asia, similar to the other two plague pandemics.
Yersinia pestis has caused at least three human plague pandemics. The second (Black Death, 14-17th centuries) and third (19-20th centuries) have been genetically characterised, but there is only a limited understanding of the first pandemic, the Plague of Justinian (6-8th centuries). To address this gap, we sequenced and analysed draft genomes of Y pestis obtained from two individuals who died in the first pandemic.
- International journal of environmental research and public health
- Published about 7 years ago
The Chinese government enforced mandatory quarantine for 60 days (from 10 May to 8 July 2009) as a preventative strategy to control the spread of the 2009 H1N1 pandemic. Such a prevention strategy was stricter than other non-pharmaceutical interventions that were carried out in many other countries. We evaluated the effectiveness of the mandatory quarantine and provide suggestions for interventions against possible future influenza pandemics. We selected one city, Beijing, as the analysis target. We reviewed the epidemiologic dynamics of the 2009 H1N1 pandemic and the implementation of quarantine measures in Beijing. The infectious population was simulated under two scenarios (quarantined and not quarantined) using a deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) model. The basic reproduction number R0 was adjusted to match the epidemic wave in Beijing. We found that mandatory quarantine served to postpone the spread of the 2009 H1N1 pandemic in Beijing by one and a half months. If mandatory quarantine was not enforced in Beijing, the infectious population could have reached 1,553 by 21 October, i.e., 5.6 times higher than the observed number. When the cost of quarantine is taken into account, mandatory quarantine was not an economically effective intervention approach against the 2009 H1N1 pandemic. We suggest adopting mitigation methods for an influenza pandemic with low mortality and morbidity.
During the early phase of the 2009 influenza pandemic, attempts were made to contain the spread of the virus. Success of reactive control measures may be compromised if the proportion of transmission that occurs before overt clinical symptoms develop is high. In this study we investigated the timing of transmission of an early prototypic strain of pandemic H1N1 2009 influenza virus in the ferret model. Ferrets are the only animal model in which this can be assessed because they display typical influenza-like clinical signs including fever and sneezing after infection. We assessed transmission from infected animals to sentinels that were placed either in direct contact or in adjacent cages, the latter reflecting the respiratory droplet (RD) transmission route. We found that pre-symptomatic influenza transmission occurred via both contact and respiratory droplet exposure before the earliest clinical sign, fever, developed. Three of 3 animals exposed in direct contact between day 1 and 2 after infection of the donor animals became infected, and 2/3 of the animals exposed at this time period by the RD route acquired the infection, with the third animal becoming seropositive indicating either a low level infection or significant exposure. Moreover, this efficient transmission did not temporally correlate with respiratory symptoms, such as coughs and sneezes, but rather with the peak viral titre in the nose. Indeed respiratory droplet transmission did not occur late in infection, even though this was when sneezing and coughing were most apparent. None of the 3 animals exposed at this time by the RD route became infected and these animals remained seronegative at the end of the experiment. These data have important implications for pandemic planning strategies and suggest that successful containment is highly unlikely for a human-adapted influenza virus that transmits efficiently within a population.
Vibrio cholerae is ubiquitous in aquatic environments, with environmental toxigenic V. cholerae O1 strains serving as a source for recurrent cholera epidemics and pandemic disease. However, a number of questions remain about long-term survival and evolution of V. cholerae strains within these aquatic environmental reservoirs. Through monitoring of the Haitian aquatic environment following the 2010 cholera epidemic, we isolated two novel non-toxigenic (ctxA/B-negative) Vibrio cholerae O1. These two isolates underwent whole-genome sequencing and were investigated through comparative genomics and Bayesian coalescent analysis. These isolates cluster in the evolutionary tree with strains responsible for clinical cholera, possessing genomic components of 6(th) and 7(th) pandemic lineages, and diverge from “modern” cholera strains around 1548 C.E. [95% HPD: 1532-1555]. Vibrio Pathogenicity Island (VPI)-1 was present; however, SXT/R391-family ICE and VPI-2 were absent. Rugose phenotype conversion and vibriophage resistance evidenced adaption for persistence in aquatic environments. The identification of V. cholerae O1 strains in the Haitian environment, which predate the first reported cholera pandemic in 1817, broadens our understanding of the history of pandemics. It also raises the possibility that these and similar environmental strains could acquire virulence genes from the 2010 Haitian epidemic clone, including the cholera toxin producing CTXϕ.
The global spread of epidemics, rumors, opinions, and innovations are complex, network-driven dynamic processes. The combined multiscale nature and intrinsic heterogeneity of the underlying networks make it difficult to develop an intuitive understanding of these processes, to distinguish relevant from peripheral factors, to predict their time course, and to locate their origin. However, we show that complex spatiotemporal patterns can be reduced to surprisingly simple, homogeneous wave propagation patterns, if conventional geographic distance is replaced by a probabilistically motivated effective distance. In the context of global, air-traffic-mediated epidemics, we show that effective distance reliably predicts disease arrival times. Even if epidemiological parameters are unknown, the method can still deliver relative arrival times. The approach can also identify the spatial origin of spreading processes and successfully be applied to data of the worldwide 2009 H1N1 influenza pandemic and 2003 SARS epidemic.
Epidemics can spread across large regions becoming pandemics by flowing along transportation and social networks. Two network attributes, transitivity (when a node is connected to two other nodes that are also directly connected between them) and centrality (the number and intensity of connections with the other nodes in the network), are widely associated with the dynamics of transmission of pathogens. Here we investigate how network centrality and transitivity influence vulnerability to diseases of human populations by examining one of the most devastating pandemic in human history, the fourteenth century plague pandemic called Black Death. We found that, after controlling for the city spatial location and the disease arrival time, cities with higher values of both centrality and transitivity were more severely affected by the plague. A simulation study indicates that this association was due to central cities with high transitivity undergo more exogenous re-infections. Our study provides an easy method to identify hotspots in epidemic networks. Focusing our effort in those vulnerable nodes may save time and resources by improving our ability of controlling deadly epidemics.
The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: pC, 0.0133-0.150 and R0, 1.09-2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with pC approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R0 and pC could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.
Epidemics and pandemics of cholera, a severe diarrheal disease, have occurred since the early 19th century and waves of epidemic disease continue today. Cholera epidemics are caused by individual, genetically monomorphic lineages of Vibrio cholerae: the ongoing seventh pandemic, which has spread globally since 1961, is associated with lineage L2 of biotype El Tor. Previous genomic studies of the epidemiology of the seventh pandemic identified three successive sub-lineages within L2, designated waves 1 to 3, which spread globally from the Bay of Bengal on multiple occasions. However, these studies did not include samples from China, which also experienced multiple epidemics of cholera in recent decades. We sequenced the genomes of 71 strains isolated in China between 1961 and 2010, as well as eight from other sources, and compared them with 181 published genomes. The results indicated that outbreaks in China between 1960 and 1990 were associated with wave 1 whereas later outbreaks were associated with wave 2. However, the previously defined waves overlapped temporally, and are an inadequate representation of the shape of the global genealogy. We therefore suggest replacing them by a series of tightly delineated clades. Between 1960 and 1990 multiple such clades were imported into China, underwent further microevolution there and then spread to other countries. China was thus both a sink and source during the pandemic spread of V. cholerae, and needs to be included in reconstructions of the global patterns of spread of cholera.