Data collected on infectious diseases, which disproportionally affect low- and middle-income countries, are often fragmented, of sub-optimal quality and use very heterogeneous methods to assess and/or analyse similar conditions. Many of the research studies include small numbers of patients, and reports or publications are often delayed or not made available, such that the data are lost to any further analysis. These deficiencies are especially acute in the context of emerging infections where initial data must be collected in the midst of a rapidly evolving situation and where patients are often geographically disparate. All of these factors contribute to production of extremely heterogeneous, dispersed data sets with few opportunities for valid comparison.
By pooling individual patient data (IPD) into harmonised platforms that integrate clinical outcomes with pharmacological and molecular information, we can circumvent many of these challenges. Analysis of larger pooled IPD increases the power to determine optimal treatments, provide evidence on the most effective outbreak responses, and can reveal differences in drug efficacy and safety over time and in specific vulnerable populations (e.g. infants, pregnant women, and patients with co-morbidities such as HIV, malnutrition, or genomic disorders), which cannot be discerned from smaller individual studies.
Currently, IDDO has these active areas of research work: malaria, COVID-19, visceral leishmaniasis, medicine quality, schistosomiasis, soil-transmitted helminthiases, Ebola, Chagas disease and antimicrobial resistance. More are already in development or being scoped for feasibility.
These platforms enable inter- and cross-discipline analysis of global data on these diseases. As a part of the platform, long-term security and accessibility of data are ensured in order to maximise utility by the health, research and humanitarian communities.
The WorldWide Antimalarial Resistance Network (WWARN) is a collaborative platform generating innovative resources and reliable evidence to inform the malaria community on the factors affecting the efficacy of antimalarial medicines. WWARN is part of the Infectious Diseases Data Observatory (IDDO).
We host one of the largest international collections of clinical data related to COVID-19 with detailed individual patient data on more than 700,000 hospitalised individuals from over 1,200 institutions across over 45 countries. IDDO has facilitated the re-use of these data in 48 novel analyses to date.
IDDO is working with the global VL research community to collate data and deliver robust science to address knowledge gaps and save lives with better treatment. To date, this collaboration has assembled a harmonised clinical trials database containing over 14,000 individual patient data (IPD), representing nearly half of the published sample size from the last 15 years.
Substandard and falsified (SF) medicines negate the multiple benefits of modern healthcare, so good quality medical products are essential. By sharing global expertise and collating information, IDDO’s Medicine Quality Research Group strengthens knowledge of the scale of the problem and raises vital awareness among key stakeholders.
Antimicrobial resistance (AMR) is a serious threat to global public health that threatens the effective prevention and treatment of a range of infections caused by microorganisms such as bacteria, parasites, viruses and fungi. AMR can result in treatment failure, prolonged illness and increased healthcare costs.
IDDO is currently scoping several new disease themes. As part of this process, IDDO conducts a scoping and feasibility assessment to gain an understanding of the clinical data landscape for that disease and whether a data platform would be of value to help advance research and answer critical questions.
Febrile illness is one of the most common reasons for healthcare visits globally. Once malaria is excluded, identifying the primary causative pathogens is restricted due to the limitations of diagnostic facilities and the scarcity of comprehensive surveillance data. In a major international study, researchers have carried out extensive systematic reviews to map the most common causes of non-malarial febrile illness across different endemic regions.