scholarly journals The Association Between Extreme Precipitation and Waterborne Disease Outbreaks in the United States, 1948–1994

2001 ◽  
Vol 91 (8) ◽  
pp. 1194-1199 ◽  
Author(s):  
Frank C. Curriero ◽  
Jonathan A. Patz ◽  
Joan B. Rose ◽  
Subhash Lele
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Disease Outbreaks ◽  
The United States ◽  
Waterborne Disease

scholarly journals A Systematic Review of Waterborne Disease Outbreaks Associated with Small Non-Community Drinking Water Systems in Canada and the United States

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0141646 ◽  
Author(s):  
Wendy Pons ◽  
Ian Young ◽  
Jenifer Truong ◽  
Andria Jones-Bitton ◽  
Scott McEwen ◽  
...  
Keyword(s):  
United States ◽  
Systematic Review ◽  
Drinking Water ◽  
Disease Outbreaks ◽  
The United States ◽  
Water Systems ◽  
Waterborne Disease ◽  
Drinking Water Systems

Food-Borne Disease Outbreaks in the United States, 1973

1975 ◽  
Vol 132 (2) ◽  
pp. 224-228 ◽  
Author(s):  
J. M. Hughes ◽  
M. H. Merson ◽  
R. A. Pollard
Keyword(s):  
United States ◽  
Disease Outbreaks ◽  
The United States ◽  
Food Borne

STAPHYLOCOCCAL DISEASE OUTBREAKS IN HOSPITAL NURSERIES IN THE UNITED STATES—DECEMBER 1971 THROUGH MARCH 1972

PEDIATRICS ◽  
1973 ◽  
Vol 51 (2) ◽  
pp. 413-417
Author(s):  
Richard E. Dixon ◽  
Richard A. Kaslow ◽  
George F. Mallison ◽  
John V. Bennett
Keyword(s):  
United States ◽  
Newborn Infants ◽  
Disease Outbreaks ◽  
The United States

Following the Food and Drug Administration's release of recommendations on limiting the use of products containing hexachlorophene (HCP) for bathing newborn infants, 142 hospitals spontaneously reported outbreaks of neonatal staphybococcal disease. Epidemiologic investigations were carried out in 73 of these hospitals; 66 had confirmed outbreaks of neonatal staphylococcal disease. In 60 of the 66, discontinuation of HCP bathing of newborn infants preceded the epidemic. Alterations in handwashing policies did not appear implicated in any outbreak investigated. These findings suggested that discontinuation of HCP bathing of newborn infants was associated with increased incidence of neonatal staphylococcal disease.

scholarly journals Phylogeographic Analysis Reveals Multiple International transmission Events Have Driven the Global Emergence of Escherichia coli O157:H7

2018 ◽  
Vol 69 (3) ◽  
pp. 428-437 ◽  
Author(s):  
Eelco Franz ◽  
Ovidiu Rotariu ◽  
Bruno S Lopes ◽  
Marion MacRae ◽  
James L Bono ◽  
...  
Keyword(s):  
United States ◽  
Disease Outbreaks ◽  
The United States ◽  
Human Case ◽  
Whole Genome Sequencing Data ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
E Coli ◽  
Phylogeographic Analysis ◽  
International Distribution

AbstractBackgroundShiga toxin–producing Escherchia coli (STEC) O157:H7 is a zoonotic pathogen that causes numerous food and waterborne disease outbreaks. It is globally distributed, but its origin and the temporal sequence of its geographical spread are unknown.MethodsWe analyzed whole-genome sequencing data of 757 isolates from 4 continents, and performed a pan-genome analysis to identify the core genome and, from this, extracted single-nucleotide polymorphisms. A timed phylogeographic analysis was performed on a subset of the isolates to investigate its worldwide spread.ResultsThe common ancestor of this set of isolates occurred around 1890 (1845–1925) and originated from the Netherlands. Phylogeographic analysis identified 34 major transmission events. The earliest were predominantly intercontinental, moving from Europe to Australia around 1937 (1909–1958), to the United States in 1941 (1921–1962), to Canada in 1960 (1943–1979), and from Australia to New Zealand in 1966 (1943–1982). This pre-dates the first reported human case of E. coli O157:H7, which was in 1975 from the United States.ConclusionsInter- and intra-continental transmission events have resulted in the current international distribution of E. coli O157:H7, and it is likely that these events were facilitated by animal movements (eg, Holstein Friesian cattle). These findings will inform policy on action that is crucial to reduce the further spread of E. coli O157:H7 and other (emerging) STEC strains globally.

scholarly journals Representing Extremes in a Daily Gridded Precipitation Analysis over the United States: Impacts of Station Density, Resolution, and Gridding Methods

2014 ◽  
Vol 27 (14) ◽  
pp. 5201-5218 ◽  
Author(s):  
Melissa Gervais ◽  
L. Bruno Tremblay ◽  
John R. Gyakum ◽  
Eyad Atallah
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
The United States ◽  
Low Resolution ◽  
Spatial Homogeneity ◽  
Precipitation Analysis ◽  
Precipitation Station ◽  
Density Resolution ◽  
Analysis Point ◽  
Station Density

Abstract This study focuses on errors in extreme precipitation in gridded station products incurred during the upscaling of station measurements to a grid, referred to as representativeness errors. Gridded precipitation station analyses are valuable observational data sources with a wide variety of applications, including model validation. The representativeness errors associated with two gridding methods are presented, consistent with either a point or areal average interpretation of model output, and it is shown that they differ significantly (up to 30%). An experiment is conducted to determine the errors associated with station density, through repeated gridding of station data within the United States using subsequently fewer stations. Two distinct error responses to reduced station density are found, which are attributed to differences in the spatial homogeneity of precipitation distributions. The error responses characterize the eastern and western United States, which are respectively more and less homogeneous. As the station density decreases, the influence of stations farther from the analysis point increases, and therefore, if the distributions are inhomogeneous in space, the analysis point is influenced by stations with very different precipitation distributions. Finally, ranges of potential percent representativeness errors of the median and extreme precipitation across the United States are created for high-resolution (0.25°) and low-resolution areal averaged (0.9° lat × 1.25° lon) precipitation fields. For example, the range of the representativeness errors is estimated, for annual extreme precipitation, to be from +16% to −12% in the low-resolution data, when station density is 5 stations per 0.9° lat × 1.25° lon grid box.

scholarly journals COVID-19: Examining the case growth-rate due to Visitor vs Local Mobility using Machine Learning: A Study in the United States

2021 ◽  
Author(s):  
satya katragadda ◽  
ravi teja bhupatiraju ◽  
vijay raghavan ◽  
ziad ashkar ◽  
raju gottumukkala
Keyword(s):  
United States ◽  
Machine Learning ◽  
Statistical Significance ◽  
Disease Outbreaks ◽  
The United States ◽  
Mobile Phone Data ◽  
Infectious Disease Outbreaks ◽  
Local Mobility ◽  
Local Risk ◽  
The Impact

Abstract Background: Travel patterns of humans play a major part in the spread of infectious diseases. This was evident in the geographical spread of COVID-19 in the United States. However, the impact of this mobility and the transmission of the virus due to local travel, compared to the population traveling across state boundaries, is unknown. This study evaluates the impact of local vs. visitor mobility in understanding the growth in the number of cases for infectious disease outbreaks. Methods: We use two different mobility metrics, namely the local risk and visitor risk extracted from trip data generated from anonymized mobile phone data across all 50 states in the United States. We analyzed the impact of just using local trips on infection spread and infection risk potential generated from visitors' trips from various other states. We used the Diebold-Mariano test to compare across three machine learning models. Finally, we compared the performance of models, including visitor mobility for all the three waves in the United States and across all 50 states. Results: We observe that visitor mobility impacts case growth and that including visitor mobility in forecasting the number of COVID-19 cases improves prediction accuracy by 34. We found the statistical significance with respect to the performance improvement resulting from including visitor mobility using the Diebold-Mariano test. We also observe that the significance was much higher during the first peak March to June 2020. Conclusion: With presence of cases everywhere (i.e. local and visitor), visitor mobility (even within the country) is shown to have significant impact on growth in number of cases. While it is not possible to account for other factors such as the impact of interventions, and differences in local mobility and visitor mobility, we find that these observations can be used to plan for both reopening and limiting visitors from regions where there are high number of cases.

Recent measles outbreaks in the United States: A look at the causes and responses

2019 ◽  
Vol 14 (10) ◽  
pp. 491-496
Author(s):  
Tracy Perron ◽  
Heather Larovere ◽  
Victoria Guerra ◽  
Kathleen Kilfeather ◽  
Nicole Pare ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Health Care Providers ◽  
Personal Autonomy ◽  
Disease Outbreaks ◽  
The United States ◽  
Care Providers ◽  
Course Of Action ◽  
Public Health Officials ◽  
Measles Outbreaks

As measles cases continue to rise in the United States and elsewhere, public health officials, health care providers and elected officials alike are facing critical questions of how to protect the health of the public from current and future vaccine preventable disease outbreaks while still preserving the religious and personal autonomy of the populations they serve. As measles cases are being examined and carefully managed, public health officials are also tasked with revisiting vaccination policies and agendas to determine the best evidence-based interventions to control this epidemic. To determine the best course of action for the public's interest, research and current literature must be examined to protect and promote the health and wellbeing of those currently affected by the measles outbreak and those yet to be exposed.

scholarly journals Simulation of Daily Extreme Precipitation over the United States in the CMIP5 30-Yr Decadal Prediction Experiment

2019 ◽  
Vol 58 (4) ◽  
pp. 875-886 ◽  
Author(s):  
Steve T. Stegall ◽  
Kenneth E. Kunkel
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The United States ◽  
Natural Variability ◽  
Return Level ◽  
Historical Period ◽  
Regional Variability ◽  
Anthropogenic Forcing ◽  
Near Term

AbstractThe CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.

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