Neglected tropical diseases (NTDs) are infections that primarily occur in regions of rural poverty in developing countries and affect more than one billion people, costing developing economies billions of dollars every year. However, some of the NTDs also occur in urban slums and favelas. The NTDs dengue fever (DF), leptospirosis and rabies are a particular cause of urban health problems in developing countries. For both DF and leptospirosis, urban flooding, at times of natural disaster, is a key component of transmission.
Several studies have shown that leptospirosis is often misdiagnosed as DF and underdiagnosed in endemic regions. DF is transmitted by mosquitoes and leptospirosis is a zoonotic infectious disease caused by Leptospira bacteria, which can be found in fresh water contaminated by animal urine. Epidemics of DF and leptospirosis have been observed following natural disasters and some of the most affected nations are disaster-prone island countries.
A clear relationship has been observed between an increase in DF cases and the southwest and northeast monsoons, particularly in Manila, in the Philippines. Moreover, leptospirosis is associated with floodwaters following monsoons. It has also been suggested that temperature and rainfall considerably increase the incidence of DF infections.
The present research is designed to shed light on the relationship between climate factors of rainfall, temperatureand relative humidity on the occurrence of DF and leptospirosis in Manila over the period January 2013– December 2014.
It is hoped that the work will provide insight into the relationship between meteorological factors and the incidence of DF and leptospirosis. The findings could also inform prevention and control of the diseases.
In this study, we investigated correlation of temporal patterns of reported numbers of laboratory-confirmed cases of both DF and leptospirosis with meteorological conditions (temperature, relative humidity, rainfall) in Manila. We used time-series analysis combined with spectral analysis and the least squares method. A 1-year cycle explained underlying variations of DF, leptospirosis and meteorological data. There was a peak of the 1-year cycle in temperature during May, followed by maxima in rainfall, relative humidity and number of laboratory-confirmed DF and leptospirosis cases
The seasonal pattern of DF data indicates large values during the wet season (June–November) with a peak in September, contemporaneous with high temperature, high relative humidity and heavy rainfall. A large peak in thenumber of leptospirosis cases was observed in September 2013, and a small peak in September 2014. The temporal pattern of temperature reveals an increase in the dry season (December–May), with peaks in April 2013 and May 2014. Thereafter, the temperature remained around 28 °C in the wet season (June–November). The seasonal patternof relative humidity indicates large values during the wet season, with peaks in August 2013 and July 2014. The seasonal pattern of rainfall shows maxima during the wet season, with a peak in August 2013. There was a smaller maximum during the 2014 wet season, with a peak in October
There was a peak in temperature during May, followed by maxima in rainfall, relative humidity and number of DF patients. We assumed that this result shows a relationship between monsoons and DF occurrence in the Philippines. In summer, temperature rises, rainfall increases with moist air transport from the ocean to continent, a monsoon begins and the atmosphere moistens, increasing relative humidity. This was followed by a peak in the number of DF patients.
We assumed that DF epidemics are correlated not only with rainfall but also relative humidity and temperature. DF during a week was related to rainfall over the prior 6–7 weeks. This can be attributed to the life-cycle duration of mosquitoes and the requirement of an adequate number of cases for spread, which is in turn affected by population density
Result suggests that DF and leptospirosis epidemics are correlated not only with rainfall but also relative humidity and temperature in the Philippines. Moreover, it suggests that DF and leptospirosis cases in Manila were influenced by monsoon occurrence. Quantifying the correlation of DF and leptospirosis infections with meteorological conditions may prove useful in predicting DF and leptospirosis epidemics, and health services should plan accordingly. Further time-series analyses of the two diseases and meteorological data in other regions of the world may elucidate their potential relationships to the monsoon or other epidemiological factors