[et_pb_section bb_built=”1″ admin_label=”Section” fullwidth=”on” specialty=”off”][et_pb_fullwidth_post_title admin_label=”Modeling disease eradication” title=”on” meta=”off” author=”on” date=”on” categories=”on” comments=”on” featured_image=”on” featured_placement=”background” parallax_effect=”off” parallax_method=”on” text_orientation=”center” text_color=”dark” text_background=”on” text_bg_color=”rgba(255,255,255,0.73)” use_border_color=”off” border_color=”#ffffff” border_style=”solid” custom_css_main_element=”padding-bottom: 10px;” custom_padding=”15%||3%|” \/][\/et_pb_section][et_pb_section bb_built=”1″ admin_label=”Section” fullwidth=”off” specialty=”off” transparent_background=”off” background_color=”rgba(12,113,195,0.16)” allow_player_pause=”off” inner_shadow=”off” parallax=”off” parallax_method=”off” make_fullwidth=”off” use_custom_width=”off” width_unit=”on” make_equal=”off” use_custom_gutter=”off” custom_padding=”0px|0px|0px|0px”][et_pb_row admin_label=”Row”][et_pb_column type=”4_4″][et_pb_text admin_label=”TEASER” background_layout=”light” text_orientation=”left” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n
Diseases evolve in response to treatment, frustrating efforts to eradicate them. In 2016 the IIASA Evolution and Ecology Program explored how evolution, population dynamics, and economic factors interact, providing new insight that could help inform efforts to control diseases like malaria.<\/strong><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=”1″ admin_label=”section” transparent_background=”off” allow_player_pause=”off” inner_shadow=”off” parallax=”off” parallax_method=”off” custom_padding=”0px|0px|0px|0px” make_fullwidth=”off” use_custom_width=”off” width_unit=”on” make_equal=”off” use_custom_gutter=”off”][et_pb_row admin_label=”Row”][et_pb_column type=”1_2″][et_pb_text admin_label=”BODY” background_layout=”light” text_orientation=”left” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n Efforts to eradicate a disease are likely to fail if medical professionals only know the target of an eradication campaign, but cannot predict the course for reaching it, according to IIASA research. The 2016 study examined the interplay between disease evolution, human populations, and economic factors to determine how diseases can be controlled, using a new, model-based view of disease eradication.<\/p>\n Despite many efforts to eliminate specific diseases, there have only been two success stories: smallpox and rinderpest. Most of the world\u2019s deadly illnesses have survived repeated efforts to eradicate them, resurging in vulnerable populations and in some cases gaining resistance to standard treatment. Malaria, for instance, infected over 200 million people in 2010, killing around 500,000 according to the World Health Organization.<\/p>\n The problem is that it\u2019s easy to make progress at the beginning, but in the last stages of eradication, when there are only a few cases, it becomes very difficult to make further progress.<\/p>\n A graph of this process would show a fast decline in the incidence of the disease, which peters out into a long tail that the researchers call an \u201ceradication tail.\u201d The reasons for this are multiple. The microbes that cause disease evolve in response to changes in their environment, sometimes gaining resistance to the drugs used against them. Likewise, eradication efforts may target the animal that spreads a disease, such as mosquitoes, which may thus evolve or adapt in response.<\/p>\n Also the way human populations are structured plays a role\u2014since diseases spread between individuals, predicting eradication tails requires mapping a population and links between diseased individuals. And crucially, economic factors contribute as well\u2014if the money for interventions runs out, the disease may come back.<\/p>\n