Historic Trends in the Secchi Disk Transparency of Lake Pontchartrain

A major environmental concern about Lake Pontchartrain is an assumed long-term increase in turbidity based on Secchi disk transparency observations. Regression of the available data on Secchi disk transparency versus time (1953 through 1990) reveals a statistically significant decrease in transparency of about 40%. However, the data set is biased in that it does not adequately represent the seasonal effects of salinity and wind speed. Two analytical procedures were undertaken to determine the extent to which the apparent long-term decrease in transparency was dependent on the seasonal bias. One procedure involved seasonal adjustment of the data for the effects of salinity and wind speed. The other procedure was to remove the seasonal bias by constructing unbiased data sets. Seasonal adjustment for the effects of salinity and wind speed reduced the level of significance for the relationship between Secchi disk transparency and time from about 1% to about 10%. This result indicates that some of the apparent decrease in transparency in the original data is the result of inadequate representation of seasonal effects in the biased data set. In most years data are not available for all months with the result that the seasonal effects of salinity and wind speed are not adequately represented. When the bias was removed by constructing unbiased data sets, the data no longer supported the conclusion of a statistically significant change in Secchi disk transparency from 1953 to 1990; p \u3e 0.5

Temporal correlation between malaria and rainfall in Sri Lanka

<p>Abstract</p> <p>Background</p> <p>Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex.</p> <p>Methods</p> <p>The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data) over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression.</p> <p>Results</p> <p>For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre-whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one) or weak negative (at lags two to six) correlations were found in pre-whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography.</p> <p>Conclusion</p> <p>Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.</p

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified