Epidemiology

Driving Global Health Equity with State-of-the-Art Epidemiology

KIT’s epidemiology team is dedicated to ensuring/promoting accessible and equitable healthcare for all, regardless of social, demographic, or epidemiological contexts. We use state-of-the-art data analyses techniques to generate evidence to optimize health interventions and to inform local and targeted health planning. With this, we generate strategic information tailored to the needs at different levels of the health system.

The team has a strong track record applying geo-spatial analysis, complex-survey-design analysis as well as innovative statistical approaches (Bayesian estimation, Artificial Intelligence) to integrate and analyze health data from various sources (e.g., Health Management Information Systems, surveys, remote sensing). While this capacity is cornerstone to the work we do, other, less complex analytical approaches and innovative data visualizations are also used to improve the understanding and uptake of our results.

Key expertise areas of the team are prevention and care of tuberculosis and neglected tropical diseases (NTD) and maternal and child health care. The team is recognized for its monitoring and evaluation approach, third party evaluations and innovative research. We support organizations in designing tailored interventions targeted to the local context to enhance access to healthcare and improve efficiency.

The following are core to our work:

Use of routinely collected health data
Strengthen health information systems
Apply, leverage and stimulate analysis and use open-source data and tools
We value mixed-methods
Adhere to good epidemiological practice (BRIDGE guidelines)
Knowledge transfer and brokering
Global partnerships.

Topics

Neglected Tropical Diseases

Read more : Neglected Tropical Diseases
Crisis & Conflict Epidemiology Lab

Read more : Crisis & Conflict Epidemiology Lab
Tuberculosis

Read more : Tuberculosis
Centre for Applied Spatial Epidemiology

Read more : Centre for Applied Spatial Epidemiology

Epidemiology courses

Geographic Information Systems (GIS) for Public Health and Epidemiology
- Institute
- Programme
Geographic Information Systems (GIS) provide tools for planning and monitoring of health interventions and disease control activities. GIS can be applied to improve health care delivery in disease control programmes. In this course you will use GIS to identify patterns of disease in time and place and to assess public access to health care services.

Read more : Geographic Information Systems (GIS) for Public Health and Epidemiology
Foundations of Monitoring, Evaluation and Learning in Public Health
- Institute
- Programme
This dynamic two-week course equips you with essential skills and knowledge to navigate the landscape of evidence-informed decision making in global public health.
This course delves into the foundational principles of monitoring, evaluation, and learning within the frame of global public health.

Read more : Foundations of Monitoring, Evaluation and Learning in Public Health
Evidence for public health responses: Statistical Methods in Epidemiology
- Institute
- Programme
This two-week course is designed to equip you with advanced statistical skills crucial for informed decision making in public health. This course delves into essential methodologies for planning epidemiological field surveys, conducting sample size calculations, and analysing complex data in R-statistical programme language, to address pressing public health challenges.

Read more : Evidence for public health responses: Statistical Methods in Epidemiology
Impact Evaluations for Health Systems Strengthening
- Institute
- Programme
Discounts and Fees We offer a range of discounts for early bird applicants, alumni, tropEd students and groups. See below the discounts and fees for Health Planning and Programming (HPP course). See for more information about our discounts for groups and other short courses on our exclusive discount page.

Read more : Impact Evaluations for Health Systems Strengthening

Our work

BRIDGE Mentorship Initiative
- Institute
- Project
The BRIDGE Mentorship Initiative is based on the BRIDGE guidelines for good epidemiological practice in epidemiology. The pilot programme has been initiated in partnership with Institute of Tropical Medicine in Belgium. Our goal is for the initiative to bring researchers conducting epidemiological studies around the globe together. Recent developments in research integrity led by researchers […]

Read more : BRIDGE Mentorship Initiative
Electronic Case based Surveillance: Using predictive modelling and real-time data to plan Active TB Case Finding in Pakistan
- Institute
- Project
Pakistan has one of the highest burdens of tuberculosis (TB) in the world, a disease that infected as many as 10 million people and caused 1.4 million deaths globally in 2019. Around a quarter of the world’s population are thought to be infected with latent TB. The disease can remain dormant for years, until, for example, the immune system is […]

Read more : Electronic Case based Surveillance: Using predictive modelling and real-time data to plan Active TB Case Finding in Pakistan
BRIDGE – Bridging Research Integrity and Global Health Epidemiology
- Institute
- Project
The BRIDGE guidelines are good epidemiological practice (GEP) guidelines specifically for global health epidemiology. Why are specific GEP guidelines needed for global health? Research integrity and research fairness have gained considerable momentum in the past decade and have direct implications for global health epidemiology. Existing good epidemiological practice guidelines developed by national epidemiological associations lack […]

Read more : BRIDGE – Bridging Research Integrity and Global Health Epidemiology
Tuberculosis Hackathon
- Institute
- Project
The Tuberculosis Hackathon begins with a question: can we make useful predictive models for sub-national tuberculosis (TB) burden in Pakistan? In partnership with Pakistan’s National Tuberculosis Control Program, KIT’s Centre for Spatial Epidemiology (CASE) is hosting a virtual hackathon to develop novel approaches to predict TB burden. The challenge TB prevalence surveys are usually powered […]

Read more : Tuberculosis Hackathon
Now more than ever, African governments need reliable data
- Institute
- Blog
- News
By Sandra Alba, Christina Mergenthaler & Roland Kielman At the end of March 2020, in an interview with the BBC, Ellen Johnson Sirleaf, the former president of Liberia, spoke about the 2014-16 Ebola outbreak in West Africa, which killed almost 5,000 Liberians. “Fear drove people to run, to hide, to hoard to protect their own,” […]

Published on: May 26, 2020

Read more : Now more than ever, African governments need reliable data
Aligning research and innovation through the European Partnership on One Health and Antimicrobial Resistance (EUP OHAMR)
- Institute
- Project
Antimicrobial resistance (AMR) is a global health challenge that affects human and animal health, food security and the environment. The European Partnership on One Health and Antimicrobial Resistance (EUP OHAMR) brings together 53 organisations from 30 countries across the EU and beyond, aiming to close knowledge gaps and break silos between sectors, disciplines and perspectives. […]

Read more : Aligning research and innovation through the European Partnership on One Health and Antimicrobial Resistance (EUP OHAMR)
Health & Prosperity – Conference Report
- Institute
- Publication
On 10 March, KIT Institute hosted the high-level conference “Health and Prosperity: How Dutch Investments in Global Health Drive Security and Economic Growth”, bringing together key stakeholders to examine the Netherlands’ investment role in global health initiatives. This event will highlight the economic and societal return on investment of Dutch contributions to global health financing, which […]

Read more : Health & Prosperity – Conference Report
Predicting communities with hightuberculosis case-finding efficiency tooptimise resource allocation in Pakistan: comparing the performance of anegative binomial spatial lag modelwith a Bayesian machine-learningmodel
- Institute
- Publication
Despite progress in tuberculosis (TB) treatment coverage in past years, an estimated 183000 people with TB may not have been diagnosed in Pakistan in 2022. Therefore, there is a need to develop models which help to steer active case finding (ACF) towards populations with a high probability of having undetected TB. The aim of this […]

Read more : Predicting communities with hightuberculosis case-finding efficiency tooptimise resource allocation in Pakistan: comparing the performance of anegative binomial spatial lag modelwith a Bayesian machine-learningmodel
Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle
- Institute
- Publication
As extreme weather events increase in frequency and intensity, the health system faces significant challenges, not only from shifting patterns of climate-sensitive diseases but also from disruptions to healthcare infrastructure, supply chains and the physical systems essential for delivering care. This necessitates the strategic use of geospatial tools to guide the delivery of healthcare services […]

Read more : Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle