supplementary data for Table S1, reviewed data of all previous cases. CMB made a critical revision of the manuscript, helped in the acquisition of data, provided supplementary data for Table S1, reviewed data of all previous cases. All authors revised and gave the approval of the final manuscript.
More than 1,000 cases of malaria are diagnosed each year in the United States. Reported numbers, however, may be artificially low because many clinicians fail to consider the diagnosis on presentation, U.S. hospital laboratory technologists have very limited experience in detecting and identifying malaria parasites, and reporting of malaria to state health departments is sporadic in many states. In this study, a rapid malaria diagnostic test, the OptiMAL test (DiaMed; under license from Flow Inc., Portland, Oreg.) was evaluated in six U.S. hospitals and compared with results of microscopy. The OptiMAL test is a 15-min rapid immunochromatographic test that both identifies and differentiates Plasmodium falciparum from non-P. falciparum malaria parasites on the basis of the detection of parasite lactate dehydrogenase in a drop of patient blood. A total of 216 specimens from patients suspected of having malaria were tested. Results indicated that 43 samples (20%) were positive for malaria parasites by microscopy (32 P. falciparum, 11 non-P. falciparum) while 42 (19%) were positive by OptiMAL (31 P. falciparum, 11 non-P. falciparum). The sensitivity of the OptiMAL test was 98%; its specificity was 100%, with positive and negative predictive values of 100 and 99%, respectively. Participating hospital physicians and laboratory directors independently reported that the OptiMAL rapid malaria test was accurate, easy to use, and well accepted by those working in their diagnostic laboratories. The overall conclusion was that integration of the OptiMAL rapid malaria test into the U.S. health care infrastructure would provide an important and easy-to-use tool for the timely diagnosis of malaria.
Ebola virus disease (EVD) is an emerging infectious disease of zoonotic origin that has been responsible for high mortality and significant social disruption in West and Central Africa. Zoonotic transmission of EVD requires contact between susceptible human hosts and the reservoir species for Ebolaviruses, which are believed to be fruit bats. Nevertheless, features of the landscape that may facilitate such points of contact have not yet been adequately identified. Nor have spatial dependencies between zoonotic EVD transmission and landscape structures been delineated. This investigation sought to describe the spatial relationship between zoonotic EVD transmission events, or spillovers, and population density and vegetation cover. An inhomogeneous Poisson process model was fitted to all precisely geolocated zoonotic transmissions of EVD in West and Central Africa. Population density was strongly associated with spillover; however, there was significant interaction between population density and green vegetation cover. In areas of very low population density, increasing vegetation cover was associated with a decrease in risk of zoonotic transmission, but as population density increased in a given area, increasing vegetation cover was associated with increased risk of zoonotic transmission. This study showed that the spatial dependencies of Ebolavirus spillover were associated with the distribution of population density and vegetation cover in the landscape, even after controlling for climate and altitude. While this is an observational study, and thus precludes direct causal inference, the findings do highlight areas that may be at risk for zoonotic EVD transmission based on the spatial configuration of important features of the landscape.
Hendra virus (HeV) is an emerging pathogen of concern in Australia given its ability to spillover from its reservoir host, pteropid bats, to horses and further on to humans, and the severe clinical presentation typical in these latter incidental hosts. Specific human pressures over recent decades, such as expanding human populations, urbanization, and forest fragmentation, may have altered the ecological niche of Pteropus species acting as natural HeV reservoirs and may modulate spillover risk. This study explored the influence of inter-decadal net human local migration between 1970 and 2000 on changes in the habitat suitability to P. alecto and P. conspicillatus from 1980 to 2015 in eastern Australia. These ecological niches were modeled using boosted regression trees and subsequently fitted, along with additional landscape factors, to HeV spillovers to explore the spatial dependency of this zoonosis. The spatial model showed that the ecological niche of these two flying fox species, the human footprint, and proximity to woody savanna were each strongly associated with HeV spillover and together explained most of the spatial dependency exhibited by this zoonosis. These findings reinforce the potential for anthropogenic pressures to shape the landscape epidemiology of HeV spillover.
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