Gene drives can be used to make mosquitoes resistant to malaria or completely eradicate a whole population. In principle, scientists are able to manipulate the fate of an entire species. Eradication approaches have not been tried outside of laboratories (though there are plans to do so as early as 2024) and there is no guarantee it will work in the wild.

Gene drives are also a matter of public acceptance and regulatory frameworks. Right now, the question of regulation is still an open one. No country in the world has had to do it yet.

Mosquitoes are not static, unchanging targets. They move around and mate, breeding in some areas but not others. Their populations grow and shrink throughout the year. They bite at different times of day. Some species stay where they are, others travel.

We need to understand these subtle quirks of mosquito life, and the full ecosystem in which they live, in order to develop the best strategy for fighting malaria.

Malaria is not just a disease commonly associated with poverty: some evidence suggests that it is also a cause of poverty and a major hindrance to economic development. If you want to successfully tackle malaria, you need to intervene in the living conditions of populations in the endemic area – individually and as communities.

In order to tackle malaria, we need a coordinated global campaign in which global health officials, government-sponsored initiatives, and private efforts like that of the Bill & Melinda Gates Foundation pull towards the same goal.

Exaptations are adaptations that have undergone a major change in function e.g. bird feathers that originally evolved for regulating body temperature are now used for flight. Research shows that mosquitos have a great capacity for exaptation and adaptation, leading to increased levels of resistance despite our efforts to combat the problem.

Knowledge of exaptation in mosquitos demonstrates the need for a multi-faceted approach to malaria. The long-term effectiveness of the current measures to prevent and tackle the disease are also called into question.

Some events are more or less likely depending on events that have happened before them – these are known as conditional probabilities. For example, young children, pregnant women, and people with weak immune systems are particularly susceptible to malaria. We know that the risk of serious complications or death is much higher for people in this group.

This sort of knowledge, concerning conditional probabilities - for example, ‘What is the probability of dying from malaria, given that someone is pregnant?’ - can help guide decision-making and lead to effective targeted intervention.

The malaria problem is exacerbated by a number of different factors, including the fact that malaria turns out to have a much greater genetic diversity than previously believed. The two most common species respond differently to medicines and exhibit drug resistance in different ways.

Moreover, the parasite itself can also evolve in ways that evade the human immune system. Even if someone contracts and recovers from malaria, that does not guarantee them protection from malaria infections in the future. This makes finding a vaccine for all types of human malaria a very difficult task.

Chaos Theory deals with nonlinear things that are effectively impossible to predict or control. In such systems, very small changes may make the system behave completely differently. This is sometimes known as the Butterfly Effect.

Malaria is subject to chaotic effects just like the rest of the world. For example, a small change in weather could cause a massive change in mosquito populations. It is important to recognise that the malaria problem is situated in a world over which we have little overall control, and where we are unable to predict the full consequences of our interventions.

We use models to understand mosquito behaviour and the ways in which we can intervene upon that behaviour. However, even our best and most useful models are limited: (A) they could be incorrect without us realising it; (B) they model is, by necessity, a reduction of the actual thing – a process in which you lose certain important information; and (C) the model needs interpretation, a process that can cause major errors.

Despite uncertainty, we need to make decisions about malaria, and we have to make them quickly to minimise suffering. To do this, we need to understand the context in which models might be useful and respect their limitations.

The control, elimination, and ultimate eradication of malaria is ambitious. This effort requires strong leadership and clear goals, as progress and impact are only possible with fruitful collaboration and communication.

People from different backgrounds and with different interests must be able to communicate effectively with each other. Without successful negotiation, no eradication programme is likely to be achieved.

Reinforcing loops cause us to steadily slip away from equilibrium by increasing the effect of a particular system or process. In extreme cases, things spiral out of control as the loop naturally amplifies and strengthens its own behaviour.

This is at the core of the malaria problem. The more people that have malaria, the higher the chance that a mosquito will pick-up the malaria-causing parasite when biting a human. In turn, this mosquito can bite another human, thus causing a new person to be infected. The good news is that the inverse is also true.