Soushieta JAGADESH

The recent pandemic of Covid19 reminds us, if it were still necessary, that the spread of infectious diseases ignores geographical boundaries. The combined changes in local biodiversity and land use, the increase in international connectivity through transport and trade, and the imminent threat of climate change have increased the risk of the emergence and re-emergence of infectious diseases (ID). Until now, the response of public health policies has been passive surveillance, but this has not proved really effective in preventing and controlling epidemics. The approach adopted here is one of anticipation, with the identification of areas at high risk of EMI based on the detection of the most favourable environmental factors. These factors include land conversion, a drastic reduction in biodiversity and climate change. The biogeographical method was used to study and analyse MPEs across different groups of pathogen taxa, including bacteria, viruses, protozoa and fungi. The study was carried out globally, as well as locally, in French Guiana, a French overseas territory located in South America. In both cases, across the different pathogen groups, the risk of flooding, the recent conversion of forest plots to farmland and the increase in minimum temperatures due to climate change were found to be significant factors in the global and local emergence of the infectious diseases studied. The main results of this thesis are as follows:

1. A biogeographical approach to modelling the distribution of IMEs using existing databases of clinical cases, satellite imagery and a non-conventional statistical model is effective for early detection of regions at risk, improving prevention and controlling their spread.
2. It is possible to anticipate MDEs by identifying and managing at an early stage the favourable factors directly linked to the anthropisation of the environment.

The COVID-19 pandemic highlights that the spread of infectious diseases goes beyond geographical boundaries. Simultaneous changes in local biodiversity and land use, the increasing international connectivity through human transport and trade and the imminent threat of climate change have increased the risk of the emergence and reemergence of infectious diseases. The current public health response to emerging infectious diseases (EID) by passive surveillance has proven largely ineffective in preventing and controlling disease outbreaks. The way towards is to "get ahead of the curve" by identifying potential hotspots of disease emergence and detecting the environmental triggers such as land transformation, biodiversity loss and climate change. I used a biogeographic approach to study and analyze disease emergence across different taxonomic pathogen groups such as bacterial, viral, protozoan and fungal, globally and in French Guiana, a French Overseas territory located in South America. I found that regions at risk of floods, recent conversion of forest to agricultural lands and increasing minimum temperature (i.e. temperature at night) caused by climate change were drivers for disease emergence locally and globally across the different pathogen groups. The main findings of the PhD thesis are the following:

1. Biogeographic approach to mapping the distribution of EIDs with using existing human cases data, remote sensing imagery and unconventional statistical models is effective to "get ahead of the curve" in the detection of regions at risk and the management of EIDs.
2. EIDs are not unprecedented but predictable by identifying and managing the triggers of disease emergence, which have a direct link with the anthropization of the environment.