Data Analysis

Currently Centers for Disease Control and Prevention (CDC) employ threshold rules to declare epidemic outbreaks, such as influenza, separately in each population. However each year influenza starts in one population and spreads population-to-population throughout the country. Therefore there is a need for an algorithm to declare the epidemic that uses information from multiple populations.

Objective

Detect epidemics over multiple Populations using computational methods

NPDS is a near real-time surveillance system and national database operated by the American Association of Poison Control Centers. NPDS receives records of all calls made to the 55 regional US poison centers (PCs). The Centers for Disease Control and Prevention (CDC) use NPDS to 1) provide public health surveillance for chemical, radiological and biological exposures and illnesses, 2) identify early markers of chemical, radiological, and biological incidents, and 3) find potential cases and enhance situational awareness during a known incident. Anomalies are reviewed daily by a distributed team of PC medical and clinical toxicologists for potential incidents of public health significance (IPHS). Information on anomalies elevated to IPHS is promptly relayed to state epidemiologists or other designated officials for situational awareness and public health response.

Current NPDS surveillance algorithms utilize the Historical Limits Method, which identifies a data anomaly when call volumes exceed a statistical threshold derived from multiple years of historical data. Alternative analysis tools such as those employed by ESSENCE and other computerized data surveillance systems have been sought to enhance NPDS signal analysis capability. Technical improvements have been implemented in 2013 to expand NPDS surveillance capabilities but have not been thoroughly tested. Moreover, other data aberration detection algorithms, such as temporal scan statistics, have not yet been tested on real-time poison center data.

Objective

To compare the effectiveness of current surveillance algorithms used in the National Poison Data System (NPDS) to identify incidents of potential public health significance with 1) new algorithms using expanded NPDS surveillance capabilities and 2) methods beyond the NPDS’ generalized historical limits model.

Currently, there is an abundance of data coming from most of the surveillance environments and applications. Identification and filtering of responsive messages from this big data ocean and then processing these informative datasets to gain knowledge are the two real challenges in today’s applications.

Use of Analytics has revolutionized many areas. At LongRiver Infotech, we have used various Machine Learning techniques (Regression, Classification, Text Analytics, Decision Trees, Clustering etc.) in different types of applications. These methodologies are abstracted in a generic platform, which can be put to use in many public health and surveillance applications, which are enumerated here.

Objective

To summarize ways in which Analytics, Machine Learning (ML) and Natural Language Processing (NLP) can improve accuracy and efficiency in bio surveillance and public health practices. We also discuss the use of this framework in typical surveillance applications (Integration with Devices/Sensors, Web/Mobile, Clinical Records, Internet queries, Social/News media).

Like in other African countries, most HIV research in Tanzania focuses on adults 15-49 years, ignoring persons aged 50 years and above. In Tanzania, the HIV testing rate (ever tested) for 15 - 49 year olds has increased from 37% to 62% for women and 27% to 47% for men between 2008 and 2012. Limited data is available on HIV testing and prevalence among older adults specifically. Some studies in Sub-Saharan Africa have, however, reported a high HIV prevalence among older people.

Objective

This study aimed to estimate socio-demographic inequalities in HIV testing and prevalence among adults aged 50+ years, living in Ifakara town, Tanzania, in 2013.

Since 2004, the French syndromic surveillance system Oscour® has been implemented by the national institute for public health surveillance (InVS) and is daily used to detect and follow-up various public health events all over the territory [1]. Beginning with 23 ED in 2004, the coverage and data quality have permanently been increasing until including about 650 ED in August 2015. Initially based on a voluntary participation of ED, a mandatory transmission has been decided in July 2013, with major modification on the structural organization of the data transmission in some regions and on coding practices of the new ED. Besides this juridical context, the system is based on automatically data collection by ED physicians without recording added information for public health surveillance. This represents the main theorical condition to ensure stability and quality, even in case of occurrence of major public health events susceptible to drastically increase the workload [2].

Objective

Identification of the main factors influencing the stability and the quality of the French Emergency departments (ED) syndromic surveillance system.

As of 2012, 3,400 000 million people (all ages) are living with HIV in Nigeria. The estimated new HIV infections is 260,000 and estimated AIDS death is 240,000.The reported number of adults on ART(Anti-retroviral treatment) was 459,465 and the ART coverage based on WHO guideline was 36%.The number of pregnant women living with HIV who received antiretroviral for preventing motherto-child –transmission was 33,323 and the percentage coverage was 17%. Enugu State has the highest prevalence (6.5%) of HIV/ AIDS in the South East and the fourth in Nigeria.To implement the commitments in the 2011 United Nations Political Declaration on HIV and AIDS and increase progress towards universal access to HIV prevention, treatment, care and support, Nigeria has developed the president’s Comprehensive Response Plan (PCRP). PCRP aims to bridge the current gap in service provision and funding. It assesses needs and gaps, identifies focus areas, and set targets for Prevention of mother to child transmission (PMTCT), ART and HIV Counseling and Testing (HCT) services. We determined the implementation of these preventive services by health care providers in Enugu State.

Objective

• To determine the percentage and trends of newly diagnosed HIV positive pregnant women

• To determine the percentage of pregnant women that are counseled tested with result.

• To determine the percentage and trend in the uptake ART among HIV positive pregnant women.

• To determine the average no of individual that are counseled and tested for HIV.

• To determine the average no of individual that are HIV positive

• To estimate the average no of individual currently on ART, newly started on ART and those enrolled into HIV care.

While the link between excess winter mortality and winter respiratory diseases in the elderly is well described, the impact of the epidemic of influenza in the elderly is mainly assessed in France through specific surveillance in the general population. Syndromic surveillance data enables to monitor ED attendances and hospitalizations for various diagnostic codes groupings throughout the influenza epidemic, some of which often cited as influenza proxies, such as cardiorespiratory diagnostic groups.

In mainland France, the 2014-15 season was characterized by an intense influenza epidemic in the community (sub-type A(H3N2) dominant virus). Hospital overcrowding was early reported, partly linked to serious clinical presentations among the elderly, and leading to the triggering of a national emergency plan.

We hypothesized that ED numbers of clinical influenza cases underestimate the influenza burden among patients aged 65 years and over, especially when a A(H3N2) influenza subtype circulates.

Objective

To estimate the real burden of influenza epidemic on emergency departments (ED) attendances and hospitalizations among patients over 65 years in order to better understand determinants of overcrowding and mortality excess.