IELTS Academic Reading Practice Test 382

In the second half of the fourteenth century, plague reached the Mediterranean, and the maritime cities that lived by trade had to decide how to protect themselves without abandoning the sea. Their answer, developed over several generations, was the lazaretto: a place apart, usually an island, where people and goods arriving from infected regions were held until the danger had passed. The system was crude, expensive and based on a mistaken understanding of how disease spread, yet it created the first organised public health bureaucracy in Europe.

The earliest surviving legislation comes from Ragusa, now Dubrovnik, a small but wealthy republic on the Adriatic coast. On 27 July 1377 its Grand Council ordered that travellers arriving from plague-stricken areas should spend thirty days in isolation before entering the city, at designated places outside it. The decree covered not only people but the goods they carried, and it appointed officials to enforce the rule. Thirty days, trentino in Italian, was the original period; it was later lengthened to forty, quaranta giorni, which is the origin of the word quarantine.

Venice, the largest port in the region, followed a different route. In 1423 the Senate granted the island of Santa Maria di Nazareth, in the lagoon, for the treatment of people already suffering from plague. It became known as the Lazzaretto Vecchio, the Old Lazaretto, and it served as a hospital rather than a place of quarantine: those who went there were not expected to leave. The name is usually traced, through Venetian dialect, to the church on the island, though other explanations have been proposed.

A generation later the republic recognised that a hospital for the sick was not enough. In 1468 it created a second station, the Lazzaretto Nuovo, on another island, and this was a true quarantine: ships suspected of carrying infection were moored there, their crews lodged in wooden huts, and their cargo unloaded and exposed to the air. The period of detention was forty days, and from the Venetian form quarantena the word passed into other European languages. The choice of forty was not based on any knowledge of how long an infection takes to develop. It was a number with powerful biblical associations, and it was long enough, in practice, for most infected ships to reveal themselves.

Quarantine required paperwork as much as walls. A vessel was supposed to arrive with a certificate issued at its port of departure, stating whether disease was present there; ships with a clean certificate might be allowed to proceed after a shorter delay, while those from an infected port faced the full forty days. In 1486 Venice set up a permanent magistracy, the Provveditori alla Sanità, three noblemen with power to close the port, isolate households and order the burning of goods.

Cargo presented a harder problem than people, because the fleets carried cloth, hides, wool and spices that could not simply be thrown away. Bales were opened, spread out and turned at intervals so that air could reach every layer. In some ports goods were also treated with vinegar or with smoke from aromatic woods, and correspondence was disinfected in the same way before delivery. None of this had any effect on the fleas that carried plague from rats to humans, but the measures did keep infected sailors away from the quayside.

Contemporary explanations of the forty-day rule reveal how little was understood. Physicians had no concept of a pathogen with an incubation period, and they attributed plague to corrupted air, to the alignment of the planets or to a disturbance in the body's humours. Forty days fitted the belief that a disease would have declared itself within that time. The rule therefore happened to be longer than the incubation period of bubonic plague, which is normally a matter of days, and so ships arriving with infected people aboard often buried them before they were allowed to dock.

The model travelled with the trade it was designed to protect. Genoa, Marseille, Ancona and numerous smaller ports established lazarettos of their own, and the word quarantine entered English in the seventeenth century. Cities varied in the length and strictness of their rules, which caused constant disputes between merchants and health officials. Ragusa's system survived until the republic itself was extinguished by Napoleon in 1808; Venice's islands remained in use into the nineteenth century, and the Lazzaretto Nuovo later served as a military depot before becoming an archaeological site.

Quarantine was also the first field in which states accepted that they had to share information. Because a ship carried a certificate from one port to another, there had to be agreement about what such a document meant, and the arguments this produced led eventually to the first international sanitary conference, held in Paris in 1851. The isolation of contacts during the SARS epidemic of 2003, and the secure facilities and health certificates of the coronavirus pandemic of 2020, would all have been familiar to a Venetian health official.

The lazaretto was not a cure and never claimed to be. It was an attempt to buy time for a city, and for four centuries it was the best that European ports could do. Its methods were based on a false theory of disease, but the principle it established — that a community may restrict the movement of people in order to protect itself — has never been abandoned.

When an unfamiliar infection begins to spread, governments ask scientists a deceptively simple question: what will happen next? The tools used to answer it are mathematical models, simplified representations of how people meet, become infected and recover. A model cannot capture every detail of a society, and it does not try to. As the statistician George Box observed, all models are wrong, but some are useful: the purpose is not to reproduce reality exactly but to compare the likely consequences of different decisions.

The first such calculation was made long before anyone knew what a virus was. In 1760 the Swiss mathematician Daniel Bernoulli presented a paper to the French Academy of Sciences on the mortality caused by smallpox and on the benefits of inoculation. His analysis suggested that universal inoculation would add years to average life expectancy, and it is often described as the first mathematical model in epidemiology. The framework still in use today was set out in 1927 by two British scientists, William Kermack and Anderson McKendrick, whose paper divided a population into three groups: those still susceptible, those currently infectious and those who had recovered or died.

This division gives the model its name, SIR. Its value lies in a single number, the reproduction number, usually written R. When nobody is immune and no precautions are taken, each infected person passes it on to an average number of others, known as the basic reproduction number, or R0. Measles is among the most transmissible of familiar diseases, with estimates of R0 commonly between 12 and 18; influenza strains are usually far lower. When the reproduction number falls below one, each case infects fewer than one other person and the outbreak shrinks.

That arithmetic explains both the alarm and the strategy. A fall from three to two sounds modest, but it changes the doubling time dramatically and can mean the difference between a health service that copes and one that does not. It also explains the idea of herd immunity: if a sufficient proportion of the population is immune, the chain of transmission is broken. The threshold is calculated as one minus one divided by R0, so a disease with an R0 of four must have three-quarters of the population protected before it stops spreading on its own.

The reproduction number is not a fixed property of a pathogen. It depends on how many people an infected person meets, how easily the infection passes between them and how long the person remains infectious. This is why the same virus produces different numbers in a crowded city and a sparsely populated island, and why behaviour matters as much as biology. A further complication is that transmission is rarely evenly distributed. A minority of cases, often called superspreaders, may be responsible for a large share of new infections, and models that ignore this pattern can misjudge what will happen.

Models differ in how much detail they attempt. Deterministic models treat numbers as smooth and predictable, which works well in large populations; stochastic models build in chance, which matters when cases are few and an outbreak might die out by luck. Agent-based models simulate millions of individuals, each with a schedule and a set of contacts, and are expensive to build. Metapopulation models divide a country into regions linked by travel, and increasingly use anonymised data from mobile phones to estimate how people move.

The most publicised modelling of recent years came from a team at Imperial College London led by Neil Ferguson, whose report of 16 March 2020 compared two strategies for a new coronavirus. One, which the authors called mitigation, aimed to slow the epidemic while accepting widespread infection; the other, suppression, aimed to drive cases to very low levels through intense restrictions. The modelling suggested that mitigation would overwhelm hospitals, and the report was widely reported to have shifted policy in the United Kingdom towards a national lockdown.

Such work is easily misunderstood. A model is not a prophecy; it is a conditional statement about what follows from a set of assumptions. If people change their behaviour, or if a new variant spreads more readily, the output changes. The data fed into the earliest models are also incomplete, because mild cases go unrecorded and testing capacity is limited, so the true number of infections may be several times the count of confirmed cases. Critics have argued that the uncertainties were poorly communicated, and that figures quoted to several decimal places gave a false impression of certainty.

Forecasters have responded by combining models rather than relying on any single one. During the COVID-19 pandemic, teams around the world submitted short-term forecasts to shared platforms, and an ensemble forecast, which took the median of the individual predictions, generally performed better than most of its components. Research now focuses on linking epidemiological models to genomic data, to records of hospital admissions and to measurements of behaviour, so that assumptions can be tested against reality as an epidemic unfolds.

None of this makes modelling optional. Every decision about schools, travel or hospitals rests on some expectation of the future, whether or not it is written as an equation. The value of the mathematics is not that it removes uncertainty, but that it shows exactly where the uncertainty lies, and what evidence would reduce it.

It has become one of the most reliable sentences in politics: prevention is better than cure. Ministers of every party repeat it, health charities print it on their leaflets, and no one in public life has ever been heard to disagree. The proposition is obviously true in ordinary life, where it is cheaper and less painful to avoid an illness than to treat one. As a guide to spending public money, however, it is almost useless, because it bundles together decisions that should be considered separately and answers none of the questions that matter.

The historical case for prevention is nonetheless strong. The great fall in death rates in industrialising countries during the nineteenth century came mainly from changes that had nothing to do with doctors: cleaner water, better sanitation, more reliable food supplies and, in the view of the medical historian Thomas McKeown, improved nutrition. McKeown's argument, set out in the 1950s and 1960s, was that medical interventions played only a minor part before the twentieth century. Later research has qualified his figures, and few historians now accept his position without reservation, but the broad pattern is difficult to dispute.

Geoffrey Rose, a British epidemiologist, supplied the most influential explanation of why. Rose observed what he called the prevention paradox: a measure that brings large benefits to the population offers little to each participating individual. Most cases of a common disease arise among the many people at moderate risk, not among the few at high risk, so a strategy aimed only at the highest-risk group will miss the majority. Rose therefore argued for shifting the whole distribution of risk, for example by reducing the salt in processed food rather than advising individual patients to eat less of it.

Thomas Frieden, a former director of the US Centers for Disease Control and Prevention, expressed a similar idea in a health impact pyramid. At its base lie interventions that require no effort from the individual at all, such as changes in income, housing and the price of unhealthy products; higher up are clinical care and, at the summit, counselling and education. The pyramid predicts that impact on the health of a population is greatest where individual effort is least, which is precisely where political resistance is strongest.

Against this, the economic argument for prevention is weaker than its advocates assume. The health economist Louise Russell examined preventive programmes in the 1980s and concluded that they frequently cost less than treating the same condition, yet rarely reduce total spending, because people who avoid one illness live longer and eventually need care for others. Screening illustrates the difficulty. A test that detects a cancer early may save a life, but it may also find abnormalities that would never have caused symptoms, leading to treatment that brings only anxiety and side effects.

Resources are finite, and the relevant comparison is between one use of money and another. England's National Institute for Health and Care Excellence has long judged treatments against a threshold of roughly twenty to thirty thousand pounds for each additional year of good-quality life, and a preventive programme has no special claim to escape that test. A screening programme that costs a great deal for each life saved may be a worse use of a fixed budget than a surgical service that costs less, even though the word prevention makes it sound more enlightened.

Equity complicates the picture further. Julian Tudor Hart, a general practitioner working in a mining valley in Wales, described what he called the inverse care law: the availability of good medical care tends to vary inversely with the need for it among the population served. The same pattern applies to prevention. Advice to eat better, exercise more and attend screening is taken up most readily by those who are already advantaged, so a programme that relies on individual choices can widen the gap it was meant to close. Prevention that changes prices, availability and working conditions narrows it.

Critics on the other side object that all this amounts to a programme for a nanny state, in which governments tax and lecture adults about how to live. The objection has force when the measures are merely symbolic. It has much less force when the intervention is a tax on tobacco, which reduces consumption among the heaviest users and raises revenue that can be spent on treatment. The choice is not between freedom and coercion but between rival forms of influence, several of which advertisers already exercise.

What would a serious commitment to prevention look like? It would mean evaluating programmes before scaling them up rather than after, protecting budgets that pay off over decades when the electoral cycle lasts four or five years, and accepting that health is produced in workplaces, schools and kitchens as well as in hospitals. It would also mean abandoning the slogan. The real question is never whether prevention is better than cure, but which preventive measures, for which people, at what cost, and compared with what alternative.

The answer is neither to give prevention a privileged place in the budget nor to leave it as a rhetorical flourish. Prevention deserves more weight than it currently receives, but the reason is not that it is always cheaper. It is that a health service which waits for people to become ill has given up on a large part of what medicine is for.