Features
Using maths to combat COVID-19
‘The pandemic has now reached a level in which no human can make an optimal decision without the aid of a computer. Therefore, we need to start working on quantitative models to identify optimal decisions, instead of pointing fingers for not making proper decisions, when decision making is literally beyond the capacity of a human.’ – Senior Lecturer, Department of Mathematics, University of Colombo,
Dr. Anuradha Mahasinghe
by Sajitha Prematunge
What has math got to do with a pandemic? At the outset, it might seem the two are completely unrelated. One has only to observe that the number of infected in certain districts is higher than that of others and making informed decisions based on those numbers could mean the difference between stifling a cluster and a full-blown third wave. Senior Lecturer, Department of Mathematics, University of Colombo, Dr. Anuradha Mahasinghe knows only too well how important the numbers are in combating COVID-19. This is why, in June, he and his colleagues proposed an optimization model, aimed at minimizing the damage to the economy, while confining the COVID-19 incidence to a level endurable by the available healthcare capacity in the country, while their compartment model projected COVID-19 transmission. Their study investigated the effectiveness of the control process with the aid of epidemiological models.
Epidemiological models
Mahasinghe explained that an epidemiological model is a model that simulates and describes an epidemic. “Modelling is essential if you want to describe a phenomenon. From the spin of an electron to the rotation of the heavenly bodies, these phenomena are understood with the aid of models. It is the models that help us describe the changes in economies and fall of financial markets,” said Mahasinghe. And pandemics are no exception. He explained that an epidemiological model, based on a reasonable theory and supported by evidence, is a collection of entities and their operations, that when put together simulate and describe an epidemic, which provides important insights into the transmission of the disease.
But how does maths factor comes in when dealing with a pandemic such as COVID-19? Mahasinghe pointed out that math is inevitable whenever dealing with numbers or quantities. “Aren’t we really sensitive to numbers in this COVID era more than ever? Every person is anxious to know the numbers of reported cases and deaths.” One might say the numbers are governing us because decisions are also made based on these numbers. However, these numbers are only the smoke, warns Mahasinghe. “One should be able to make a better decision if he sees the fire. Therefore, to make the best decisions during the pandemic you have to look into a mathematical model that can best describe the phenomenon.”
Numbers may govern us but what governs the numbers? According to Mahasinghe, this can only be uncovered by a model that captures the quantitative aspects of the pandemic. “It’s what we call a mathematical model which provides us with an explanation to the occurrence of these numbers.” Such a model can also forecast how these numbers are going to change in the future.
But how credible are these models? Hopefully, they are nothing like the local weather forecast. “Such models are based upon very fundamental and well-accepted laws in nature such as energy conservation, which cannot be falsified,” reiterated Mahasinghe. “Such models are supported and validated by empirical evidence. People use such models very often to make decisions in industry to make profit. So, why not look into the numbers and the math behind them to make optimal decisions accordingly, in a pandemic scenario?”
Where we went wrong
When asked where Sri Lanka went wrong in attempting to contain the pandemic, Mahasinghe said, “I guess we didn’t see the fire, we only saw the smoke. More precisely, we didn’t pay enough attention to the transmission dynamics or to optimal decision making. We were able to make some good decisions in a qualitative sense, but I seriously doubt we had the insight to make quantitatively sound decisions.” He pointed out that even when the decisions were made, the outcome could not be predicted due to a lack of a mechanism to forecast.
When asked whether the authorities were too quick to lift the lockdown, Mahasinghe answered in the negative. “I don’t think it was too early. Lifting strict lockdowns was essential at that moment. We were struggling to achieve two conflicting goals; containing the disease and sustaining the economy. Stepping down from strict curfew to partial lockdowns is indeed a good decision in such a context.” But was it methodical? Was there a mechanism to decide on the nature of the partial lockdowns? Did we know how to optimally restrict mobility in order to achieve those conflicting goals? Did we know to what extent the lockdown of a district should be optimally eased? Did we estimate the potential increase in positive cases from a district when its lockdown would be relaxed? Did we know the magnitude of the economic loss caused by shutting down a region? These are questions Marasinghe believes that authorities should have paid attention to, when easing the lockdown.
“Lockdowns could have been relaxed with the aid of proper optimization models capable of providing answers to these questions.” He repeated that such models are used very often in industrial decision making and provide promising solutions. “You can’t bring the COVID incidence down to zero even with such models, but at least you know what’s going on and the effectiveness of a decision so the health sector can take relevant measures.
According to Mahasinghe, authorities have overlooked the significance of data. “Even now I don’t think enough attention is paid to data.” According to him, some important data were not gathered. For example, he pointed out that, despite Western Province residents being advised against crossing borders, some invariably did, as there were no strict rules against it. “There is no point in regretting the fact, but we could have counted the number of vehicles that crossed the borders and used it to estimate the impact on transmission.”
He explained that the entire country can be regarded as an epidemiological network, where the nodes are the cities and the interconnections are the roads. “There are elegant models in network theory to gain many insights into transmission through such a network.” He also noted another pertinent issue, that even if data were gathered, they were not used. “Much effort was made to gather and organize COVID related data such as incidence per region etc, and that is really commendable. However, have we used them; what were the insights we gained into transmission from them except for some trivial speculations?” questions Mahasinghe. He reiterated that such insights can only be gained through an extensive study that involves the collaboration between mathematicians, computer scientists, epidemiologists and economists. “The mathematician’s part alone includes exhaustive algorithmic development and computational modelling challenges,” explained Mahasinghe.
Criteria
When asked what factors were taken into consideration in their optimization model, Mahasinghe reminded that a delicate balance must be struck between two conflicting goals. “We need to find the optimal compromise between containing the disease and sustaining the economy. As a developing country, we can’t afford beyond a certain level of the control process, so budgetary constraints must be considered.” It is obvious that COVID-19 is transmitted through human mobility. He pointed out that, consequently, inter-regional travel plays a significant role. “On the other hand, transmission dynamics can be modelled to a certain extent by well-known compartment models. However, human mobility affects the compartments and the relevant model has to be moderated accordingly to reflect that reality.” The optimization model considers all factors, such as medical capacity to deal with the pandemic, economic concerns, transmission dynamics, regional contribution to the economy, and generates a lockdown relaxation strategy that keeps the level of incidence below a desired threshold, while minimizing damage to the economy.
However, Mahasinghe pointed out that this was a prototype and it can be made closer to reality by incorporating more constraints. “For instance, I haven’t considered the fact that most agricultural activities are done in the North Central province. But, if required, that too can be incorporated without difficulty.” According to him epidemiologists and economists can introduce more constraints to the optimization model, and the applied mathematician’s job is to overcome the computational challenges posed by incorporating them.
Relevant?
There is no point in closing the stable doors after the horse has bolted. Months after the lifting of the lockdown are such models even relevant? “The compartment model that captures the transmission of COVID-19 is still applicable, irrespective of any lockdowns, unless it is quite certain that there is absolutely no community transmission. I think we were in such a stage only at the very beginning of the first wave,” said Mahasinghe. According to him, the network-based model that captures human mobility is also applicable irrespective of lockdowns or any other preventive measures. In contrast to these, the optimization model is applicable in its existing form only when lockdowns are in force. “Having said that, this model may still be useful with some changes in the present context where small regions are isolated. For instance, a slightly changed variant of that model can determine which areas should undergo isolation. Moreover, it is possible to modify the optimization model further to be used in the process of making decisions on identifying the persons to be quarantined.”
Human mobility is a critical factor in the spread of a pandemic as well as any models targeted at managing such, how could a mathematical model factor this in? “Not only COVID-19 but even dengue is transmitted mainly due to human mobility. A mosquito doesn’t travel very far during its lifetime. Humans are more responsible for carrying diseases.” Mahasinghe pointed out that COVID-19 is not very different. “If you know the way humans move from place to place, and also know the level of incidence in each place, it is not that difficult to model how the disease is transmitted through humans.” He observed that most preventive measures are also focused on restricting human mobility, which he deemed commendable. “A mathematical model can prescribe the optimal way to restrict mobility.”
What are the implications of mobility? For example are people of certain districts more inclined to travel and therefore may contribute more to the spread of the disease and are such implications reflected in the numbers? “As long as the model is deterministic and you can overcome the computational challenges by necessary algorithm development, closed-form and conclusive solutions can be generated.” Mahasinghe implied that math helps to see the big picture. “Consequences of travel from the Western to other provinces is obvious. However, considering the transport network, Southern and North Western Provinces are also at high risk.” He observed that less attention has been paid to those regions. This begs the question, are the Southern and North Western provinces a time bomb waiting to go kaboom? He reiterated that special attention must be paid to regions that are relatively less danger, such as North Central, which contributes significantly to economic growth, as the Western province is not capable of contributing to the economy in its full capacity. “It is important to keep the incidence at a low level in such places.”
The study predicted that easing lockdown in the Western Province would have adverse repercussions. “As long as vehicles cross inter-provincial barriers, the disease is transmitted to those regions. But in what magnitude? We had access to certain transport data, so we knew to a certain extent how people would mobilise within the country. Also the epidemiological data were available. So we had enough inputs to be fed into our algorithm.” The results were appalling. In fact, this computer experimentation was done in the early days when Sri Lanka was hit by the first wave and there were no strict measures to curtail inter-provincial mobility. During the days in question, Mahasinghe ranked the provinces according to their vulnerability to COVID-19, using another model, by adopting some ideas from network theory. Recently, upon perusing a map that indicated the countrywide spread of the disease Mahasinghe came to realize that the ranking has been validated, eventually. “What I don’t understand is why we failed to foresee this.”
Mahasinghe and his team had access to certain transport data, such as the number of buses, trains and bus routes. However, his models were prototypes. To make the prediction more accurate they would need current transport data, such as the number of private vehicles crossing provincial borders. “There are a number of police barriers between borders, so a vehicle count would not be impossible. If health planners are willing to use that type of model, these could be extremely valuable datasets.”
Quantifying the qualitative
In their model they quantify the degree of social distancing. But can criteria so human in nature be quantified? Moreover, how can something as complex as a pandemic, with so many variables, human in nature, be simplified into ones and zeroes? Mahasinghe maintained that it is possible to estimate the degree of social distancing observed, if provided with sufficient data. “I understand that it sounds quite unrealistic. It is because we think of individuals.” Mahasinghe emphasised the importance of noting that they are not modelling an individual, but rather a population. “Though a population consists of individuals, the dynamics of the population is not merely the sum of the dynamics of an individual. When you single out a person, the behaviour of that person is surely very uncertain and unpredictable. Take two persons, they may have certain things in common, so it is not that unpredictable. If you take a thousand people, a lot of commonalities can be extracted and the situation becomes predictable now.” He explained that, therefore, it is possible to assign a value to the degree of distancing with the aid of necessary data.
“Interestingly, it is true that we mathematicians seek certainty in an uncertain world. However, an event that looks uncertain from one point of view looks certain from another.” The toss of a coin is a simple example. “If you toss a coin, the outcome of it being head or tail is widely believed to be uncertain. However, it is the lack of data that makes it uncertain. Suppose the initial speed, the weight, the angle of projection and such were provided, then the outcome may be predictable by basic equations of motion.” Mahasinghe emphasised that math does not guarantee elimination of uncertainty. “That is definitely not the direction the mathematical sciences are moving, specially with the recent developments in quantum physics and unconventional computing. However, where macroscopic events like pandemics or human behaviour are concerned, there are many certainties that we misinterpret under the cover of uncertainty due to our lack of knowledge, eventually missing an opportunity to gain crucial insights into the scenario.”
Mahasinghe pointed out that many decisions are binary in nature. Let alone policy decisions, many behavioural decisions are inherently binary. “For instance, you may decide whether to wear a mask or not. So the one-zero nature of the action is inherent and not artificially imposed by a mathematician.” He further explained that some non-binary decisions can still be quantified. “For instance, if you decide to wear the mask on three days and go unmasked on four days of the week, it can be quantified using numbers and interpreted using probability.” Mahasinghe elaborated that, with recent developments in non deterministic models, applied mathematicians do not hesitate to incorporate uncertainty. “Consequently, uncertainty is no longer immeasurable. It is possible to confine uncertainty of the solution within reasonable limits.
What next
With all the talk on vaccination, Mahasinghe emphasised the importance of developing two mathematical models prior to vaccination. The first is a compartment model that explains the post-vaccination dynamics of the disease. “This is pretty standard in mathematical epidemiology. The second, developing a model to capture the effects of the interactions between individuals and predict the outcomes, is subtler and challenging.” He explained that once a phase of vaccination is over, persons in society can be divided into two categories: vaccinated and unvaccinated. “Take a random encounter between two persons. What type of interaction would it be? Is it a vaccinated encountering another vaccinated, an unvaccinated encountering another unvaccinated or a vaccinated encountering an unvaccinated? Obviously, the consequences of these encounters are essentially different.”
The discipline of mathematics referred to as game theory is a promising tool in modelling this type of scenario and forecasting the outcomes. In addition, once vaccination commences, there will be the issue of free riding. Due to different reasons, some people in the high risk category will also choose to remain unvaccinated, eventually resulting in a significant number of potential free riders. Mahasinghe explained that this has already been addressed in the game theory in particular, under evolutionary games. “As a nation we can’t be content with an elementary formula for herd immunity. Instead, we need to develop and upgrade elegant vaccination strategies using compartment models and game theory.” Mahasinghe is of the view that, in this pre-vaccination phase, these two are the immediate concerns that need to be addressed by applied mathematicians.
Benefits
When asked what are the drawbacks of not using a mathematical model are and the benefits of using one, Mahasinghe pointed out that in a scenario of conflicting goals and monetary restrictions, it is impossible to make decisions without seeing where the optimal compromise is. “It is easy to put the blame on politicians and other policy makers for not making the right decisions, but how can a human make an optimal decision in this entangled web of parameters, conflicting goals and constraints? Plainly speaking, we need computers to generate the best decisions for us.” That’s indeed what the computers are intended to do primarily, according to Mahasinghe, although they are more frequently used to watch YouTube videos and log into Facebook!
But to perform the intended task using a computer, models and algorithms that can be read by the computer must be created. “That’s why you need to look into optimization, mathematical programming, computational modelling and game theory. This way, you may be able to keep the numbers within certain limits. Also, you can pre-assess a decision quantitatively. Our health workers and armed forces have already committed much and continue to do so and to receive the full benefit of their commitments, the willingness to switch from qualitative to quantitative methods, is essential.
When asked if such models are used successfully in other countries to counter the pandemic, Mahasinghe answered in the affirmative. Since the very beginning, an extensive mathematical modelling process has been done and that’s how the predictions were made. In fact, vaccination models had long been applied to control epidemics even in African countries. In Sri Lanka, there are many misconceptions about mathematical models.” Mahasinghe has observed certain non-mathematicians presenting elementary regressions, numerical approximations and statistical tests, erroneously referring to them as mathematical models.
“Perhaps that’s why some policy makers have lost faith in math. As mentioned earlier, a mathematical model is based on an unfalsifiable conservation law. It cannot be compared to a trivial curve fitting cakewalk. Our people get easily carried away by exotic words. People tend to admire words like machine learning, artificial intelligence and such, but how many are aware of the maths behind these words?” He observed that a closer examination of news reports on machine learning or AI being used in some country to counter the pandemic, would reveal that they are mathematical models and machine learning techniques are used due to the toughness of generating a closed-form solution. “Even to apply computational heuristics, the problem has to be formulated mathematically. Correct problem formulation is a major component of a so-called AI-powered decision.
Mahasinghe explained that the subject of operations research emerged in the new industrial era to enable industrial decision making using computers, as the number of industrial parameters exceeded human ability to process. “The pandemic has now reached this level so that no human can make an optimal decision without the aid of a computer. Therefore, we need to start working on quantitative models to identify optimal decisions, instead of pointing fingers for not making proper decisions, when decision making is literally beyond the capacity of a human.”
Features
Investing in ecosystems
Biodiversity is the sum of all the patterns of life that nature creates in biomass
An ecosystem is defined as a geographic area where biotic (living) organisms—plants, animals, microorganisms interact with each other and with the abiotic (non-living) components like air, water, sunlight, and soil, creating a self-sustaining unit of life. A pond with its attendant diversity is the ecosystem that supports pondlife, from frogs to fish or dragonflies, while an ocean is an ecosystem that supports fish to whales. So, it will be seen that ecosystems and their components change with scale. This creates a challenge for investment, what is the scale chosen for investment in the ecosystem?
In terms of biodiversity, ecosystems represent an evolutionary process over geological time, to sustain life through climate extremes. Over the span of existence, life forms and consequently their ecosystems have developed to be responsive to changes and represent the most successful combination of species in that environment.
On a geographic scale they manifest today as tropical rainforest or as temperate peatland or Andean paramo, each displaying a unique biodiversity complex that enables sustainability of that ecosystem in that place. These patterns suggest that the form and function of any resident ecosystem can provide a guide for designing restoration programmes and activities in that environment.
During the last two centuries, the landscapes of Sri Lanka were subject to massive changes. The total destruction of the montane forests, removed both above ground and below ground biomass. Fire cleared the land of standing vegetation, followed by the erosion of eons of topsoil. The forests were replaced with monoculture plantations which were very low in biodiversity. A response to address this loss of forest biodiversity was proposed as a ‘tree dominated ecosystem analogous to the lost native forest’. This system was tested and codified as Analog Forestry. In this process the structure and function of the original forest is used as the baseline for creating a tree dominated ecosystem.
Why should we try to mimic forests? Forests produce oxygen, filter water, cool landscapes, support biodiversity and provide renewable biomass as critical ecosystem services. In addition, forest soils contain one of the most species rich ecosystems on the planet, full of microbial life, while at the same time acting as a repository of organic carbon that stores moisture and substrate. Yet conventional financial systems treat the destruction of this productive infrastructure as a negative externality to the cost of doing business, forcing the environment to bear the cost. The pollution output of industry is an example. Similarly, the loss of ecosystem services was ignored as a negative externality to the cost of establishing plantations. It is the accumulation of these externalities that has brought us to the present crisis in environmental sustainability.
Analog Forestry seeks to reclaim some of the lost ecosystem services by establishing a tree-dominated ecosystem that is analogous in architectural structure and ecological function to the original climax or sub climax vegetation community. This vegetation complex may comprise natural or exotic species in any proportion, the contribution to creating an ecosystem analogous in structure and function, being a major factor that determines its design. The ecological functions of the system can be measured by a number of variables. The most critical being an understanding of the architecture that evolves in any ecosystem progressing through the process of seral succession. After this, functions within this ecosystem can be addressed. Some examples are; the ecological function of providing microhabitat, keystone species, stabilizing nutrient cycles, or maintaining trophic flows.
Analog Forestry also draws on the strengths of traditional knowledge. Many traditional responses mimic the structure or succession process of their local forest vegetation. The use of successional stages of natural ecosystems to design cropping systems have been recorded in many traditions. Analog Forestry encourages further complexity into the structure of such cropping systems, thus creating space for many species of the original forest to extend their ranges, either by design or effect.
As the species composition in each design varies according to different production goals, species utilised are selected from a comprehensive database.
It is in the output of this ecosystem where value can be generated and a platform for investment can be offered. Currently, only the farm product entering the economy has value in the market. The farm ecosystem has no value. One way to increase both biodiversity and rural income is by value addition through certification systems confirming clean, responsible production as in organic or regenerative agriculture. However, the true value of the contributions of ecosystem services generated by the farm, remain opaque to the economy.
The global economy operates on a fundamental accounting error: it classifies the depletion of natural capital as a “negative externality” to the cost of any process in creating a product. Thus, pollution of air, water or soil are considered negative externalities, with no responsibility by the consumer.
A useful response to this negative trend is to consider creating a product that enhances natural capital through actions such as oxygen production, water purification, climate regulation, soil formation or biodiversity maintenance.
These activities generate positive externalities into the environment and have been recognised for what they are, Ecosystem Services. Current economic models place the global value of ecosystem services at exceeding $145 trillion annually, substantially exceeding global GDP. However, these services remain invisible on current institutional balance sheets.
An early attempt at utilising ecosystem services was the capitalisation of biomass through the voluntary carbon and biodiversity credit market. Driven by net-zero commitments, mandatory ESG disclosure frameworks, which are part of the reporting frameworks used by companies for the disclosure of data covering business operations, were developed; They address opportunities and risks that are related to environmental, social and governance (ESG) aspects of business. The Kunming-Montreal Global Biodiversity Framework’s 30×30 conservation targets, which mandates signatory nations to effectively conserve and manage at least 30% of the world’s terrestrial, inland water, and coastal and marine areas by 2030, while simultaneously placing 30% of degraded ecosystems under active restoration, create a demand for high-integrity environmental credits. This demand has been accelerating at a pace at which the existing market infrastructure cannot adequately serve. The combined addressable market across carbon, biodiversity, water and ecosystem credits are projected to exceed $370 billion by 2035.
The regulatory frameworks driving this growth such as the TNFD a global, market-led initiative that provides organisations with a risk management and disclosure framework to identify, assess, manage, and report on their nature-related dependencies, impacts, risks, and opportunities, or the CSRD a new European law that requires organisations to report sustainability information on an annual basis, are already in force.
Analog Forestry provides opportunities for investment in the ecosystems that it creates by providing high value outputs across a range of ecosystem services. For example,the high values placed on carbon sequestration services in the carbon market, could create designs in the floral architecture to provide the greatest aboveground biomass. Such designs could also provide effective cooling of the ambient atmosphere through transpiration. The application of Analog Forestry promotes the growth of organic soils that increase the water retentivity value of that land. A further output is the conservation of biodiversity facilitated by trophic and microhabitat creation.
Investment in such processes requires the setting and monitoring of standards in regard to the chain of custody in the supply of crops to markets or for conservation of biodiversity. In Analog Forestry such a standard was instituted by the International Analog Forestry Network (IAFN) in response to the demand for a certification system that conforms to the philosophy and principles of Analog Forestry. This system of certification, termed Forest Garden Products (FGP), has been functioning for over 20 years and standards maintained by the IAFN. The certification confirms clean production and biodiversity conservation.
A more complete evaluation of the ecosystem is one that combines all the value fractions of a land, this has been introduced by AQUAE Labs as the Aquae Labs Ecosystem Conservation Index (ALCI). It has been presented as the world’s first scientifically rigorous, field-validated set of measurement protocols for the financial recognition of natural capital. This system measures ecosystems as living, productive, regenerative infrastructure—and converts their verified output into institutional-grade, tradeable, insured digital assets. Their protocols are available to any interested person.
Thus, environmentally restorative activity has a large potential for generating business opportunities, ranging from investment in data secure tokens to trading in a diverse range of products and outcomes, Analog Forestry provides an example of a production design for the direction ahead.
by Dr. Ranil Senanayake
Features
In the shadow of the Pacific: Decoding El Niño within a landscape of local scepticism
In the tea-scented hills, the sprawling paddy fields of the dry zone, in various types of daily conversations, academic disclosures at very high levels, extremely loud political discussions in all areas of our Motherland, and even in the crowded markets of Colombo, a single phrase of foreign origin has begun to circulate with the ominous weight of a prophecy: El Niño. It is talked about as a vile harbinger of impending doom.
To many Sri Lankans already battered by years of economic turbulence, as well as unreliable and incompetent political governance, the warnings issued from global climate monitors and the Department of Meteorology of our island, sound just like the dastardly plot of a dystopian novel. We are told that from about July 2026, the island would face an unprecedented climate threat: a major drought capable of drying up reservoirs, decimating crops, and crippling an already fragile power grid.
Yet for all that, as the rhetoric heats up, so does public scepticism. In a nation aimlessly navigating through a severely bruised rupee, skyrocketing costs of living, erratic transport costs, and an endless cycle of political scandals, a collective weariness has set in. It is completely natural to ask: “Is this climate crisis real? Or is it merely a well-timed political smoke screen, a government ploy designed to divert our gaze from systemic corruption, economic mismanagement, and the everyday struggle to survive?”
To find the truth, we must separate genuine meteorological science from political convenience and understand that nature’s cycles have been profoundly altered by the modern world.
Framework of a Distant Monster: What really is El Niño?
El Niño
, which is Spanish for “The Boy Child,” named by Peruvian fishermen who noticed the warm ocean currents peaking around Christmas, is not a sudden, man-made disaster or an unpredictable catastrophe that is profoundly inevitable. It is one half of the El Niño-Southern Oscillation (ENSO) Cycle; the planet’s most powerful natural climate driver. Under normal conditions of the globe, strong trade winds blow from East to West across the equatorial Pacific Ocean, pushing warm surface water towards Asia and Australia, while deep, cold, nutrient-rich water wells up along the South American coast.
During an El Niño event, these trade winds weaken or even completely reverse. The pool of warm water sloshes backwards, migrating toward the Americas. This shift alters the atmospheric circulation across the entire globe, shifting jet streams and flipping weather patterns upside down. Where there was rain, there is drought; where there was dry air, there are torrential floods.
The weakening of the trade winds does not happen spontaneously. Instead, it is the result of a massive, fragile feedback loop between the ocean and the atmosphere known as the Bjerknes Feedback. We need to think of the Pacific Ocean as a giant bathtub. Normally, trade winds push all the warm water to the West (near Asia), leaving cold water in the East (near South America). Because the West is warm, it creates rising air, clouds, and low pressure. Because the East is cold, it creates sinking air and high pressure. This pressure difference is what keeps the winds blowing.
An El Niño event begins when this loop encounters a disruption. Deep in the Western Pacific, sudden, intense bursts of wind blowing from the West (opposite of normal trade winds) occur. These are often triggered by natural weather phenomena, like the Madden-Julian Oscillation, described as a massive band of rain and wind that circles the globe every 30 to 60 days.
Then there is the Oceanic Wave. These wind bursts push a massive, subsurface wave of warm water, called a Kelvin Wave, in the direction of the East across the Pacific. As this warm water moves East, it warms the cold Eastern Pacific. The result thereof is that because the East is now warm, the temperature and pressure difference between the East and the West shrinks. With the pressure difference gone, the trade winds collapse completely.
It is not spontaneous, but it is uncontrolled. It is a self-regulating, natural oscillation. The Earth’s climate system builds up heat over time. Think of the tropical Pacific as a solar heat collector. Eventually, it traps more heat than it can distribute normally. El Niño acts like a planetary pressure release valve. It releases the trapped oceanic heat into the atmosphere, which is why global temperatures spike during an El Niño year. Once the heat is dissipated, the system naturally resets, often swinging to the opposite extreme called La Niña, where trade winds become violently strong and the Eastern Pacific becomes abnormally cold, before returning to neutral.
It is totally reasonable to look at something as massively disruptive as El Niño and wonder if human hands are pulling the triggers, especially given how much we have messed with the planet’s ecosystems. Man’s actions are NOT directly responsible for triggering El Niño, but we are guilty of intensifying its impacts. Because of human-induced greenhouse gas emissions, the oceans have absorbed over 90% of excess global heat. Therefore, when a natural El Niño develops today, it is operating on a much hotter baseline. A “strong” El Niño today causes far more severe heatwaves and droughts than what an El Niño did 100 years ago. In addition, while human stupidity does not directly cause the weather pattern, political negligence, corruption, and deforestation make us completely defenceless against it. Nature creates the drought; human mismanagement creates the famine.
An El Niño event does not just randomly occur; it is highly predictable, but only up to a certain point in time. Meteorologists use a massive network of deep-sea buoys, satellites, and advanced computer models to track sub-surface ocean temperatures. Because those Kelvin Waves take months to travel across the Pacific, scientists can see an El Niño incident brewing even six months before it actually changes the weather on land.
For Sri Lanka, sitting in the warm embrace of the Indian Ocean, this remote shifting of the Pacific engine behaves like a massive atmospheric vacuum. By mid-2026, the developing El Niño is projected to significantly weaken our Southwest Monsoon (Yala season). The moisture-laden winds that usually drench the western slopes and central hills are disrupted, leading to prolonged dry spells, suppressed rainfall, and soaring temperatures: an impending doom of unpredictable severity.
The Mirage of the “Natural Cycle”
A frequent and valid argument raised by sceptics is that Sri Lanka has always survived droughts. Our ancient civilisation was entirely built upon a sophisticated cascade of tanks (Wewas) engineered by our ancient Kings to balance the natural cycles where rain and flood inevitably follow dry spells. Why should 2026 be any different?
The answer lies in a dangerous convergence: the intersection of a natural cycle with an unnaturally altered planet. Historically, El Niño events occurred in predictable intervals of two to seven years. However, decades of global greenhouse gas emissions have trapped immense thermal energy within the world’s oceans. When an El Niño occurs today, it acts on top of a baseline global temperature that is already higher than at any point in recorded human history. It injects a massive burst of heat into an atmosphere that is already supercharged.
Furthermore, our local buffering systems have been systematically dismantled. The natural cycles of nature rely on healthy ecosystems to self-regulate. Decades of rampant deforestation in our central catchments mean that when rain does fall, the soil can no longer retain it; it washes away as flash floods, leaving the land parched shortly after.
Our ancient tank systems are heavily silted due to unchecked agricultural runoff and poor maintenance, dramatically reducing their storage capacity. Today, our population has increased many times over since the last great historical droughts. The margin for error has vanished. When a dry spell hits in 2026, it is no longer just a meteorological event. It becomes an immediate, high-stakes threat to our collective survival.
The Dual Faces of the Peril: “Climate Whiplash”
The relationship between El Niño and Sri Lanka’s climate is highly complex and profoundly uneven. It is quite a hazardous oversimplification to state that the entire island will simply dry up into a desert. In reality, scientists warn of a phenomenon known as “climate whiplash”, a brutal, two-phase sequence that tests different parts of the island in different ways.
This dual nature makes preparation immensely difficult. While the western agricultural zones face severe water stress during the crucial Yala growing season, the Eastern and Northern Plains may experience a stronger-than-normal Northeast Monsoon later in the year, threatening the Maha harvest with floods rather than lack of water.
Compounding this is the impact on marine life. The disruption of oceanic currents halts the upwelling of cold, nutrient-rich waters along our coasts, threatening the phytoplankton populations that form the foundation of our fishing industry. A crisis in the ocean quickly transforms into a livelihood crisis for our coastal communities.
A Convenient Shield: Is the Government likely to exploit the “Crisis”?
Given the undeniable scientific reality of El Niño, why does the suspicion of a “government ploy” remain so stubbornly entrenched in the public psyche?
The truth is that while the weather phenomenon is entirely natural, the political exploitation of it is a time-honoured strategy. For an administration presiding over a heavily depreciated rupee, staggering inflation, fuel shortages, and an electorate deeply disillusioned by systemic corruption and unethical political behaviour, a looming natural disaster is a highly convenient distraction.
Historically, political regimes globally have utilised “disaster capitalism” and the rhetoric of impending doom to achieve three distinct political objectives:
1. Shifting the Blame:
Politicians can attribute economic misery, power outages, and food shortages to an “act of God” rather than years of policy failures, financial scams, and a lack of long-term planning.
2. Consolidating Control:
Under the guise of national crisis management, governments can divert public funds, bypass standard procurement transparency, and suppress public dissent or protests regarding living costs. They can even use draconian laws nonchalantly to quell protests.
3. Securing Foreign Aid:
Crying “imminent drought” acts as a powerful tool to solicit international foreign aid and concessions. Such a step could secure foreign exchange that can prop up a failing currency.
It is a most unfortunate but quite q realistic tragedy of loss of faith that, when our leaders shout “drought,” the citizens do not see a proactive state protecting the public. Politicians are perceived as villains looking for an exit strategy from their own defaults and scandals. The public cynicism is born out of a well-earned, deeply ingrained suspicion: one that is based on abundant past experience.
Bridging the Divide: Real Science Meets Justified Anger
We must not let political pessimism blind us to physical reality. The rising temperatures, the drying up of rural wells, and the global oceanic data, are not fabrications cooked up in a political campaign office; they are verifiable facts measured by independent scientists worldwide.
If we dismiss El Niño as a mere myth, we play directly into the hands of the very politicians we distrust. Total apathy ensures that when the agricultural yields drop, when food prices skyrocket further, and when the power grid fails due to a lack of hydropower, the public will be left entirely unprotected, while the political elite remain insulated in their air-conditioned enclaves.
The real challenge facing Sri Lanka in 2026 is a dual crisis: we are being forced to battle a volatile climate anomaly while simultaneously navigating a severe governance deficit.
The Path Forward: Demanding Accountable Resilience
Surviving the coming months requires a radical shift in how we view governance and climate preparation. We must transform our justified anger into an unyielding demand for transparency and structural resilience.
=Dynamic Energy Management: With hydropower severely threatened by drying reservoirs, the state must immediately diversify our energy mix. This means removing the bureaucratic hurdles that have historically stalled private solar and wind initiatives, often held back to protect corrupt coal and heavy fossil fuel monopolies as well as political henchmen.
= Decentralised Water and Food Security:
Rather than waiting for centralised, state-led distribution networks that are historically prone to corruption and inefficiency, local provincial councils must be empowered. Investment must be funnelled into rehabilitating local cascades, scaling up regional rainwater harvesting, and accelerating tech-driven solutions like the Thalaiyadi desalination efforts in parched Northern Zones.
= Transparent Climate Audits:
If the state claims it requires funds to mitigate El Niño, the civil society and independent media MUST demand a line-by-line public accounting of every rupee spent. If food is imported to offset local crop failures, the procurement processes must be completely transparent to prevent the predictable scams that have plagued past crises.
El Niño
is a very real possibility in the months to come, and its atmospheric mechanics are entirely beyond our control. We could only pray that we will be spared to th greatest extent possible. There is the distinct possibility that the power dynamics of nature could even be completely inverted by a force that could even be similar to the energy associated with the movement of a tectonic plate. Recently there have been a lot of opinions presented by many people, including so-called “experts”, and “pundits”,, pontificating on the likely impact of El Niño on our resplendent isle. These have varied from projected rather innocuous and tame effects on Sri Lanka, to some of them escalating the impact to major disastrous effects on the island. As usual, politicians of all hues have even waxed eloquent, most of them at the top of their voices, on the perceived potential effects of this likely natural calamity.
Yet for all that, even in the face of all the water that has gone under the bridge (pun unintended), it is vital to understand that the impact of an El Niño affair on our lives would be determined completely by human action, policy, preparedness, strategy implementation, and, of course, absolutely candid integrity. We cannot stop the Pacific Ocean from warming. However, we can prevent our institutions that need to deal with the phenomenon from sinking down to vile behaviour patterns, and even stimulate the deteriorating as well as decaying essential response portals.
The ultimate “litmus test” for Sri Lanka in 2026 is not merely whether we can survive a natural dry spell. The real, true, and candid trial for all of us would be the ultimate result as to whether we can be resilient enough to withstand the projected volatile developments of nature, while severely holding accountable the political forces that have left us ever so vulnerable to all types of quirks of nature, as experienced by the management of natural disasters even in the not-too-distant past.
By an Aficionado
Features
Tales of Mystery and Suspense – episode 6
Dark Fire
From a tale set just over a 100 years ago, I move back several centuries to one set in the 16th century, in the reign of Henry VIII. This was given to me by my friend Daniel Moylan – Lord Moylan I should say, which is how he was announced when he came to see me in the flat of a friend in London. He had mentioned enjoying tales of a Tudor detective, and when I expressed interest, he brought me the second in the series. The first had introduced the hero, a hunchback lawyer called Mathew Shardlake, who worked for Thomas Cromwell, Henry VIII’s Chief Minister after the fall of Cardinal Wolsey. Here, too, it is Cromwell who gets Shardlake to find out more about a secret weapon that had been brought to his notice.
The book by C J Sansom, is called Dark Fire and this refers to fire that in Byzantine days could be projected onto enemies and their equipment, notably ships, to set them immediately ablaze. But the secret had been lost, except that it seemed that a soldier, back from the east, had brought home a barrel of the stuff, which had been discovered in one of the monasteries that Henry VIII had dissolved.
Two shady individuals, including a lawyer called Gristwood, had told Cromwell about the weapon and given him a demonstration, which led him to tell the King that he could see the fire in action in a couple of weeks. But the lawyer Gristwood had torn off the formula from the document describing the weapon, and Cromwell asked Shardlake to persuade Gristwood to hand it over.
He forces Shardlake to agree by involving himself in a case Shardlake had taken on to defend a young girl, Elizabeth Wentworth, accused of having murdered her cousin in whose house she was dwelling after she had been orphaned. Joseph, her oldest uncle, who loved her, thought she would do better in town with his rich brother Edwin rather than on his farm, but she hated the house and its inhabitants, and they were all determined, including her grandmother, who was blind but dominated the household, to have her found guilty, after she was found near a well in which her cousin had drowned and his sisters said she had pushed him in.
She refuses to plead, and the judge orders her to be pressed, a form of torture, which would soon have cost her life, but Cromwell sends a trusted servant to get the judge to suspend the sentence for two weeks. And the servant, Jack Barak, tells Shardlake that he must now see Cromwell, who says that the price of the girl’s freedom is finding out Gristwood’s secret.
After this convoluted beginning, the story moves swiftly. Gristwood and his brother are found murdered. Shardlake and Barak realise they are dealing with ruthless men, and Gristwood’s wife and the librarian who had given Gristwood information about the old soldier, are taken into safe custody by Cromwell. The wife, meanwhile, tells Shardlake about Gristwood’s mistress, and they go to a brothel to find her but she flees with her brother, having evidently been sought out previously by the murderers.
Finally, the youngsters agree to meet Shardlake, but when they get to Gristwood’s house, as had been arranged, they find the boy killed, and the girl so injured that she soon dies, though not before having told Shardlake that Gristwood had told her that his contacting Cromwell was part of a plot against him.
Meanwhile, Shardlake has also been working on his own case, and realises that the key to that mystery was the well, from which there had been a foul smell when the body of the boy was brought out. This was by the house steward, who is the confidante of the family, and fancied it seemed by one of the two sisters of the murdered boy.
Shardlake and Barak explore the well on two separate nights, fleeing the first time when dogs are set loose, but also because Barak is horrified by what he seems to see there. The next time he confirms that there were dead animals there, and also the body of a little boy. And after he had managed to get Elizabeth to speak, if obliquely, she then makes it clear that these were victims of her cousin, who had been aided in his cruelty to animals by his sisters.
Shardlake has many narrow shaves from the two murderers, who follow him to the different places he has to visit, and who seem to have a source of information about what he thought was known only to him and Barak and Cromwell. He does wonder then about the three intermediaries through whom Gristwood had got his story to Cromwell, two lawyers and an aristocratic lady whom Shardlake begins to fancy, feeling that his interest is reciprocated.
To his relief she is not the traitor, nor is the lawyer who had vanished for a couple of days, though the other – who had been feared dead when his ring was found on a dismembered finger, near Lincoln’s Inn, where they all practised – was implicated along with the fountainhead of the plot, who was determined to bring down Cromwell.
So he turns up at the climax, which comes in a shed by the river where Shardlake and Barak are trapped. But after the plotters have told them what they had done, they escape since Shardlake had a dagger which Barak uses to cut his bonds, and in the scuffle the chief murderer is killed. His accomplice had died earlier, having fallen off the top of the cathedral, where he had been cornered by Shardlake and Barak, after a hectic chase.
Before the principal murderer in Dark Fire was killed by Barak, the chief plotter had left. The lawyer who had been his principal accessory was caught but before he could be taken to Cromwell, he tried to kill Barak when he was off guard. He was only stopped by Shardlake shooting the last remains of Dark Fire at him, and him being set alight by a candle so that he threw himself into the Thames.
The evidence then is gone but Shardlake and Barak have no doubt that Cromwell will believe them, and they go to his office. He is away, but his secretary says he will send a message, and the two go back home, to rest, after Barak’s wounds have been attended to, by the physician Guy, who had, one gathers, assisted Shardlake also in the first book about him.
They are surprised when there is no word from Cromwell the following morning, but they have decided that they must now go to the Wentworth home to conclude that case. The father of the murdered boy is not there, but they go to see his mother, who is with the steward. She seems to realise the game is up, and having invited them to have a drink she confesses to what had happened.
But Shardlake then realises that he has been poisoned, though he has the presence of mind to remember that Guy had told him an emetic was the answer, and he swallows some mustard and is sick, as Barak is to whom he passes the mustard pot. The steward flees, for Barak has his sword in his hand, and before the pair collapse the grandmother rises in a panic and knocks her head against a wall when she stumbles and falls.
Shardlake had managed to call for a constable before he falls senseless, and had managed to tell the constable who comes in to get Guy, who attends to the two men. The steward is caught, and a magistrate is brought in to take depositions. Edwin is distraught, for he knew nothing of what had gone on, and his brother Joseph tries to comfort him, evincing the goodness that had made Shardlake take on the case in the first place.
The story comes out at the court hearing the next day, and the crusty old magistrate has to acquit Elizabeth and arraign the grandmother and the two sisters. But when Shardlake and Barak go to the Inns, they find that Cromwell has fallen. The Catholics are now in the ascendancy, and Shardlake and Barak leave London, though since the reaction is mild, they get back a few months later. They find that the grandmother has died, and the two sisters have been imprisoned for the murder, for one of them had pushed the boy in, and then both had concealed this and tried to blame Elizabeth.
Shardlake resumes his practice, with Barak now his assistant. His former assistant, who continues though he now needs more support, had turned out to have bad eyesight, which Shardlake had not noticed. Barak had brought this to his attention, which made him realise that underneath the rough exterior was a sensitive soul. And as the extract from the next novel indicates, they will be a pair, on Holmes and Watson lines, or Poirot and Hastings.
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