TY - JOUR AU - Morbey, Roger AU - Elliot, Alex J. AU - Loveridge, Paul AU - Hughes, Helen AU - Harcourt, Sally AU - Smith, Sue PY - 2017/05/02 Y2 - 2024/03/29 TI - “That was then, this is now” improving public health syndromic surveillance baselines JF - Online Journal of Public Health Informatics JA - OJPHI VL - 9 IS - 1 SE - Novel algorithms, statistical or mathematical methods DO - 10.5210/ojphi.v9i1.7600 UR - https://ojphi.org/ojs/index.php/ojphi/article/view/7600 SP - AB - <div style="left: 90px; top: 340.758px; font-size: 14.1667px; font-family: sans-serif; transform: scaleX(1.08129);" data-canvas-width="63.778333333333336">Objective</div><div style="left: 105px; top: 355.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.994285);" data-canvas-width="378.22591666666665">To improve the ability of syndromic surveillance systems to detect</div><div style="left: 90px; top: 372.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00097);" data-canvas-width="87.35166666666665">unusual events.</div><div style="left: 90px; top: 404.091px; font-size: 14.1667px; font-family: sans-serif; transform: scaleX(1.11768);" data-canvas-width="82.63416666666666">Introduction</div><div style="left: 105px; top: 419.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.980029);" data-canvas-width="378.0134166666666">Syndromic surveillance systems are used by Public Health England</div><div style="left: 90px; top: 435.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.01872);" data-canvas-width="394.14358333333325">(PHE) to detect changes in health care activity that are indicative of</div><div style="left: 90px; top: 452.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.965233);" data-canvas-width="395.2145833333332">potential threats to public health. By providing early warning and</div><div style="left: 90px; top: 469.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.962212);" data-canvas-width="394.73149999999987">situational awareness, these systems play a key role in supporting</div><div style="left: 90px; top: 485.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.991081);" data-canvas-width="395.5900000000003">infectious disease surveillance programmes, decision making and</div><div style="left: 90px; top: 502.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00079);" data-canvas-width="218.79000000000008">supporting public health interventions.</div><div style="left: 105px; top: 519.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.987221);" data-canvas-width="250.11249999999987">In order to improve the identification of</div><div style="left: 355.229px; top: 519.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.11571);" data-canvas-width="49.147">unusual</div><div style="left: 404.405px; top: 519.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.981134);" data-canvas-width="81.28691666666667">activity, we</div><div style="left: 90px; top: 535.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00273);" data-canvas-width="198.75833333333335">created new baselines to model</div><div style="left: 288.678px; top: 535.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.06442);" data-canvas-width="123.80958333333334">seasonally expected</div><div style="left: 412.434px; top: 535.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.98633);" data-canvas-width="73.74458333333332">activity in</div><div style="left: 90px; top: 552.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00347);" data-canvas-width="395.8506666666667">the absence of outbreaks or other incidents. Although historical</div><div style="left: 90px; top: 569.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.998201);" data-canvas-width="395.96966666666714">data could be used to model seasonality, changes due to public</div><div style="left: 90px; top: 585.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00504);" data-canvas-width="395.98666666666645">health interventions or working practices affected comparability.</div><div style="left: 90px; top: 602.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.03559);" data-canvas-width="394.5246666666666">Specific examples of these changes included a major change in the</div><div style="left: 90px; top: 619.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.02852);" data-canvas-width="394.64225">way telehealth services were provided in England and the rotavirus</div><div style="left: 90px; top: 635.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.980015);" data-canvas-width="395.4851666666665">vaccination programme introduced in July 2013 that changed the</div><div style="left: 90px; top: 652.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.99664);" data-canvas-width="393.3573333333333">seasonality of gastrointestinal consultations. Therefore, we needed to</div><div style="left: 90px; top: 669.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00074);" data-canvas-width="296.2533333333332">incorporate these temporal changes in our baselines.</div><div style="left: 90px; top: 700.758px; font-size: 14.1667px; font-family: sans-serif; transform: scaleX(1.07287);" data-canvas-width="58.23916666666666">Methods</div><div style="left: 105px; top: 715.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.01225);" data-canvas-width="378.91725">We used negative binominal regression to model daily syndromic</div><div style="left: 90px; top: 732.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.962067);" data-canvas-width="394.76833333333354">surveillance, allowing for day of week and public holiday effects.</div><div style="left: 90px; top: 749.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.01484);" data-canvas-width="393.9438333333333">To account for step changes in data caused by changes in healthcare</div><div style="left: 90px; top: 765.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.97904);" data-canvas-width="393.0357499999999">system working practices or public health interventions we introduced</div><div style="left: 90px; top: 782.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.999766);" data-canvas-width="393.32474999999994">specific independent variables into the models. Finally, we smoothed</div><div style="left: 90px; top: 799.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.967433);" data-canvas-width="394.9383333333335">the regression models to provide short term forecasts of expected</div><div style="left: 90px; top: 815.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00171);" data-canvas-width="38.165">trends.</div><div style="left: 105px; top: 832.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.05985);" data-canvas-width="382.64166666666677">The new baselines were applied to PHE’s four syndromic</div><div style="left: 90px; top: 849.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00575);" data-canvas-width="393.8007499999999">surveillance systems for daily surveillance and public-facing weekly</div><div style="left: 90px; top: 865.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00088);" data-canvas-width="52.34583333333333">bulletins.</div><div style="left: 90px; top: 897.425px; font-size: 14.1667px; font-family: sans-serif; transform: scaleX(1.08488);" data-canvas-width="51.17">Results</div><div style="left: 105px; top: 912.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.972634);" data-canvas-width="379.86216666666684">We replaced traditional surveillance baselines (based on simple</div><div style="left: 90px; top: 929.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.990969);" data-canvas-width="395.95833333333326">averages of historical data) with the regression models for daily</div><div style="left: 90px; top: 945.709px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.990069);" data-canvas-width="395.5489166666667">surveillance of 53 syndromes across four syndromic surveillance</div><div style="left: 90px; top: 962.376px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.01274);" data-canvas-width="394.07558333333327">systems. The improved models captured current seasonal trends and</div><div style="left: 90px; top: 979.043px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00318);" data-canvas-width="312.37499999999994">more closely reflected actual data outside of outbreaks.</div><div style="left: 90px; top: 1010.76px; font-size: 14.1667px; font-family: sans-serif; transform: scaleX(1.10336);" data-canvas-width="85.01416666666667">Conclusions</div><div style="left: 105px; top: 1025.71px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.11403);" data-canvas-width="387.3279999999999">Syndromic surveillance baselines provide context for</div><div style="left: 90px; top: 1042.38px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.984348);" data-canvas-width="392.73825">epidemiologists to make decisions about seasonal disease activity and</div><div style="left: 90px; top: 1059.04px; font-size: 14.1667px; font-family: serif; transform: scaleX(0.968715);" data-canvas-width="394.8320833333332">emerging public health threats. The improved baselines developed</div><div style="left: 90px; top: 1075.71px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.0337);" data-canvas-width="394.5275000000001">here showed whether current activity was consistent with expected</div><div style="left: 90px; top: 1092.38px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.00578);" data-canvas-width="393.6775">activity, given all available information, and improved interpretation</div><div style="left: 90px; top: 1109.04px; font-size: 14.1667px; font-family: serif; transform: scaleX(1.002);" data-canvas-width="230.94500000000008">when trends diverged from expectations.</div> ER -