Background and Core Problem

Liberia, West Africa is low income country that has lived through the consequences of weak outbreak preparedness. The 2014–2016 Ebola outbreak https://www.cdc.gov/mmwr/preview/mmwrhtml/mm63e1114a4.htm placed enormous pressure on the country’s health system and showed that safe, reliable laboratories are essential for early diagnosis, outbreak response and public trust.

Since Ebola, Liberia has made important progress. The National Public Health Institute of Liberia (NPHIL) https://www.nphil.gov.lr/ has become a central institution for surveillance, laboratory coordination and emergency preparedness. The National Public Health Reference Laboratory (NPHRL) in Monrovia (Liberia) plays a key role in the country’s public health laboratory system.

But serious biosafety and biosecurity gaps remain. World Health Organization's 2023 Joint External Evaluation (JEE) https://www.afro.who.int/sites/default/files/2024-05/Liberia%202023%20JEE%20Report.pdf of Liberia’s core capacities rated biosafety and biosecurity as very weak areas (score 1/5). It identified gaps in policy, oversight, training, equipment maintenance, pathogen accountability and sustainable systems. In simple terms, Liberia still needs stronger routines to make sure laboratory work is consistently safe, secure and ready for outbreaks.

What this project will do?

This project will address one practical problem: Liberia needs a simple, usable way to identify biosafety and biosecurity gaps at the laboratory level and turn those findings into a clear action plan.

The project will create and pilot BLAM - Biosafety and Biosecurity Landscape Assessment Matrix.

BLAM will be a practical tool that breaks biosafety and biosecurity into clear areas, such as:

• governance and oversight

• pathogen accountability

• incident reporting

• specimen handling and referral

• staff training and competency

• biosafety routines

• biosecurity practices

• sustainability and follow-up.

Instead of only saying “capacity is weak,” BLAM will help show where the gaps are, which gaps matter most, and what should be improved first.

The project will focus mainly on the National Public Health Reference Laboratory (NPHRL) situated in capital city Monrovia (Liberia, West Africa) with attention to how it connects with selected county-level laboratory functions and referral pathways. This will keep the project realistic for a small seed grant while still producing learning that can support future scale-up.

The project will also connect this work to AI safety. AI tools are becoming easier to access and may soon be used by laboratory staff to draft SOPs, summarize technical guidance, prepare reports, translate documents or troubleshoot routine problems. This could be useful, but it could also create risks if AI gives incorrect advice, if sensitive laboratory information is entered into unsafe tools, or if there is no process for checking AI-generated guidance.

For this seed project, AI will not be used to make biosafety decisions. Instead, the project will prepare the ground for future work by asking: what basic biosafety and biosecurity systems must be in place before fragile laboratories can use AI safely?

This makes BLAM useful in two ways. First, it will help Liberia identify current biosafety and biosecurity gaps. Second, it will create a platform that can later be expanded into an AI-readiness and AI-biosecurity assessment module.

The goal of this project will be to develop and pilot BLAM as a practical, Liberia-relevant tool for identifying biosafety and biosecurity gaps and preparing an evidence-based pathway for future strengthening.

The project will not try to solve all of Liberia’s laboratory biosafety problems. It will create the tool and evidence needed to make the next phase fundable, better targeted and nationally useful.

Activities

• Review the evidence: It will use Liberia’s JEE 2023 findings, national laboratory documents, biosafety guidance and relevant policies to define the main areas BLAM should assess.

• Develop the BLAM tool: It will create a simple matrix with domains, indicators, scoring guidance and evidence requirements.

• Pilot BLAM in Liberia: It will test BLAM at the National Public Health Reference Laboratory and selected linked laboratory functions or county referral points, depending on access and approval.

• Engage local stakeholders: It will involve NPHIL, laboratory staff, public health leaders and relevant partners to check whether the tool is practical and useful.

• Identify priority gaps: It will produce a clear picture of the most important biosafety and biosecurity gaps that need future investment.

• Prepare a scale-up pathway: It will develop a short, funder-ready plan for expanding BLAM to more laboratories and possibly adding an AI-safety module in a later phase.

Outputs

The project will produce:

• working version of BLAM

• short BLAM scoring guide

• Liberia biosafety and biosecurity scoping report

• list of priority gaps and “no-regrets” actions

• simple implementation pathway for the next 12–24 months

• concept note for future scale-up funding

• initial outline for adding an AI-readiness module to BLAM later.

The most important output will be BLAM itself: a practical assessment tool that can be improved, reused and scaled.

Why this matters for global health security and AI safety?

Biosafety and biosecurity are basic foundations of pandemic preparedness. If laboratories cannot safely handle, refer and manage infectious specimens, outbreaks can be detected late, staff can be exposed, and public health response can be delayed.

This matters beyond Liberia. Infectious diseases do not stay within borders. Strengthening biosafety in one fragile health system contributes to regional and global health security.

It also matters for AI safety. As AI becomes more capable, it may enter biological work faster than policies and safety systems can adapt. Countries with fragile laboratory systems may be especially vulnerable because they often have fewer layers of oversight, fewer trained staff and weaker reporting systems.

This project will not solve AI-biosecurity risk directly. But it will build the first layer: a way to understand whether the basic biosafety and biosecurity system is strong enough to safely absorb future AI tools.

The future question will be:

Can laboratories use AI safely if they do not yet have strong incident reporting, pathogen accountability, equipment maintenance and verification systems?

BLAM will help answer that question.

This is a seed project. The purpose will be to test whether BLAM is useful, not to implement a national programme.

How I plan to use the funding?

A small grant of USD 10000 will be required to develop the tool, conduct initial field engagement, hold focused meetings, support local logistics and allow me to dedicate time to the work as an unfunded PhD researcher.

The project will reduce uncertainty for future funders. It will show whether BLAM can produce practical findings, whether Liberian stakeholders find it useful, and what a larger implementation phase should look like.

The funding will mainly support:

• local logistics in Liberia

• meetings with laboratory and public health stakeholders

• transport and communication costs

• development of the BLAM tool and scoring guide

• preparation of the scoping report

• my protected time to design, conduct, analyze and write up the project as an unfunded PhD researcher

• preparation of the scale-up concept note.

The funding will not be used for large equipment purchases, laboratory renovation or broad national implementation. Those will require a later scale-up grant.

Future scale-up pathway

If this seed project is successful, it will create a strong basis for additional funding from Manifund, AI-safety funders and others.

A future phase could:

• expand BLAM to more county laboratories

• include animal, environmental and One Health laboratory interfaces

• digitize BLAM for easier data collection and reporting

• develop an AI-biosecurity module

• test whether AI can help summarize BLAM findings safely

• develop safe-use guidance for AI in public health laboratory work

• support NPHIL and partners to turn BLAM findings into practical investments.

The long-term aim will be to move from a small pilot to a Liberia-owned system for identifying, prioritizing and addressing biosafety and biosecurity risks.