Out break of disease

The city called Caffa, in the Crimea, in present day Ukraine which was a stronghold of Genoese merchants, when it became under attack by Mongol armies, as it had been several times before. An attack in 1344 had shown the city to be nearly impregnable, but it was now two years later and something was different; this time the bubonic plaque accompanied the armies form central Asia. The invading Tartar soldiers were being decimated by the disease, and they also faced an acute sanitation problem caused by the accumulation of dead bodies. Military genius came to their aid. The mongols had brought along a kind of strong catapult; it was ordinarily used to hurl heavy loads of stone to destroy defencses such as masonry walls and towers. Now, not stones but human missiles rained down upon those behind the walls. An eye witness wrote in a latin manuscript that the mountains of dead were soon joined by many of the Chrisitian defenders, while those who were able to escape fled the stench and the disease.

The story of Caffa is not just an early case of germ warfare. Some historians and epidemiologists believe that this particular battle marks the starting point of the the plague’s invasion from central Asia into Europe. The Genoese who fled to Europe may have brought the bacteria back in rats on their ships, and in the rats’ fleas. What ever the original source, the great European plaque of 1348 certainly emanated from mediterranean port cities. From accounts written by monks and from parish death records, we know it went on to kill somewhere between 25 to 50% of the European population. However, the exact route by which the black death came to Europe will never be known for certain.

The bubonic plaque happened centuries ago, but the questions it posed then are still with us today. Why do epidemics breakout and why cant scientists predict the size, location, and timing of the next outbreak of an old disease, such as influenza or measles, or the coming of AIDS? The diffculty lies in creating accurate scientific models of infection, rather like predicting the weather relies on decent models of the atmospheres and oceans. Epidemics occur when certain chains of events occur; each event has a certain probability of occuring and, as a consequence, an average or expected frequency of occurrence. To predict epidemics, we need to have accurate mathematical models of the process. Modeling involves knowing the steps in the chain and the probability of each one. Then the expected outcome of the whole series of steps can be estimated, in essence by multiplying together all the probabilities and numbers of people involved in a particular scenario. A closely related example of chain reaction mechanism is the way gossip spreads throughout the workplace. Gossip, though has something more profoundly in common with the spread of disease. You hear a piece of information and pass it on to a couple of trusted confidants, they may repeat it as well. After a few person to person transmissions, the message is rarely the same as the beginning. When you hear the story a month later you will recognize it as a garbled version of the original. In the language of genetics, the gossip has mutated and, like a disease that mutates, it can then reinfect someone who had caught the original disease. This happens with influenza, for which the vaccine has to be reformulated each year in order to be effective against newly appearing strains of the disease.

Chains of events are used to understand many important processes in the sciences. The same model consisting of successive probabilities and producing estimates of overall outcomes governs the chain reaction in nuclear physics. A chain reaction can be sustained when the atoms in a radioactive substance emit particles, and each atom’s particles split on average one atom in turn, causing further particle emission, and so on. These emitted particles can be very important even when they are not being usd to provoke a chain reaction. Radioisotopes have been put to great use in medicine, because certain radioactive materials are attracted to particular bones, organs, or tissues when injected or ingested. The mathematics that governs chain reactions is the same as that governing the course of epidemics, because each person or atom must affect the next one in order for sustained transmission to occur. Early on in uman history, large epidemics rarely happened as human populations were sparse. People infected with communicable diseases could not on average meet and infect one susceptibe, therefore epidemics tended to die out quickly. For any given population size, the fraction of people who are susceptible to a disease is a key influence on the ultimate size of an epidemic. Smallpox was not an indigenous disease among the tribes native to north America, so none had the immunity conferred by the experience of even the mildest smallpox infection and killed them in great numbers during late 1763.for diseases with vectors other animals that carry the disease to humans – the steps needed for the chain of causation may have been identified and scientifically demonstrated beyond the shadow of a doubt, as in the case of plague. The life cycles of the organisms involved are known in detail. Yet the uncertainties around our estimates of each parameter are so great, and the likelihood of the estimate being accurate is so small, that prediction is impossible.