Correlational Study of the Prevalence of Dengue,

Leptospirosis and

Rainfall in the National Capital Region

MV R. Angeles1, KA A. Balazuela2, R L. Crisostomo3, CL A. Custodio4, MG P. De Torres5,

BI T. Mercado6, PM C. Solis7

Department of Biology, School of Science and Engineering, Ateneo de Manila University

Loyola Heights, Quezon City, Philippines 1108

vienna112095@yahoo.com1, katherine.balazuela@obf.ateneo.edu2, lauriangeli@yahoo.com.ph4

marla.detorres@obf.ateneo.edu5, bianca.mercado@obf.ateneo.edu6, patrisce.solis@obf.ateneo.edu7

______________________________________________________________________________

ABSTRACT

The correlation between the amount of precipitation in the Philippines and the prevalence

of Dengue and Leptospirosis is investigated in this study. The area of concentration will only be

limited to the National Capital Region (NCR) in the Philippines. The data to be used will be taken

from government institutions due to the constriction of time and limited resources for self-testing.

Using various statistical methods, such as correlational, inferential and descriptive statistics, a

relationship between the given variables will be established or invalidated. The Statistical

Package for the Social Sciences (SPSS) will be the primary software to be utilized. The Pearsons

Correlation Method will also be used to determine the presence and strength of the relationship.

Morbidity data will be the basis for the timeline of comparison. It is concluded that there is no

significant relationship between the amount of rainfall and the prevalence of Dengue and

Leptospirosis in the country. This implies that the diseases involved occur regardless of changes

in weather.

Keywords: dengue, leptospirosis, precipitation, rainfall, correlational statistics, inferential

statistics

INTRODUCTION

For the past twenty years, dengue has been part of the top ten causes of morbidity in the

Philippines with cases reaching up to an average of 16, 490 cases from 2002-2006. On the other

hand, the number of leptospirosis cases reached up to 2, 789 in August 2012 (Disease

Surveillance Report). The cases of leptospirosis are at its peak during the months of July to

November. During the same time, dengue cases are also at their peak. In a clinical study by

Mishkra et al. (2013), it states that dengue and leptospirosis have similar symptoms such as high

fever and rashes especially during the initial phase and severe forms of these diseases.

Dengue hemorrhagic fever (DHF) is due to a viral infection by four serotypes which are

DEN1, DEN2, DEN3 and DEN4. It is very common in urban areas, as the vector of this disease,

the Aedes aegypti mosquito, thrive in these areas during daytime and prefer to feed on blood of

humans. Vaccine for this disease is not yet available to the public as clinical trials for the

developed sample in Thailand has not yet commenced(Gubler and Clark 1995).

On the other hand, Leptospirosis is a common zoonosis worldwide and is due to the

spirochete Leptospira. It doesnt only affect humans but other mammals too such as dogs, cattle

and swine. The general symptoms of this disease are the onset of fever, renal and hepatic

insufficiency. One of the most common way of getting the disease is through the vector Mus

musculus (common name: mouse) that releases the bacteria from its body through its excrements

(Adler and Moctezuma 2010). The leptospirosis epidemic in tropical countries is often related to

heavy rainfall and flooding (JECH, 2004). In relation to this, studies have taken into account

the fact that the presence of environmental factors, including weather variable, may play a

significant role in transmission of dengue - the major parameters being temperature, rainfall, and

humidity (Jaroensutasinee 2013). The latter study producing results stating that

Monthly rainfall, the number of rainy days, daily maximum

rainfall, relative humidity, and min/mean temperature, at a

lag between zero to three months, were positively associated

with dengue incidence in Sisaket over the study period - Jaroensutasinee (2013)

Thus, it is the desire of our study to examine and further prove the correlation of dengue

to rainfall, leptospirosis to rainfall, and dengue to leptospirosis.

Considering the regularity of flooding and formation of puddles, as well as other sources

of stagnant water during the rainy season wherein the amount of rainfall is elevated, it is

presumable that the precipitation levels are directly proportional to an extent to the frequency of

Dengue and Leptospirosis in the Philippines.

MATERIALS AND METHODS

The prevalence figures were collected from the Disease Surveillance Report from the

Department of Health website. The data gathered only consisted of morbidity weeks spanning the

year 2013 (Figure 1). The type of data is only concerned with the prevalence of the leptospirosis

and dengue occurring in the National Capital Region. This denotes that only the people

implicated by disease is part of the count, not the people who have died. This is regardless of age,

gender, and specific location within the region.

To present descriptive data, Microsoft Excel 2010 was used. Analysis of the numerical

data gathered was done using the Statistical Package for the Social Sciences (SPSS) software,

using linear regression analysis. Furthermore, the Pearsons Correlation Method was used to

determine the presence and strength of the relationship.

RESULTS AND DISCUSSION

Table 1. Morbidity Weeks and their Corresponding Values in 2013

Table 2. The prevalence of leptospirosis and the average amount of rainfall during the given

morbidity weeks

Figure 1: Line graph showing relationship between leptospirosis and rainfall

Table 3. The prevalence of dengue and the average amount of rainfall during the given morbidity

weeks

Figure 2: Line graph showing relationship between dengue and rainfall

The raw data that was gathered from the websites needed were processed and analyzed.

On Table 2 and Figure 1, it describes the trend of leptospirosis and the amount of rainfall

according to the progression of the morbidity weeks. On the other hand Table 3 and Figure 2

describes the trend of dengue and the amount of rainfall according to the progression of the

morbidity weeks. In both diseases, it is seen that on week 34, the average amount of rainfall is at

its highest with a value of 34.3 mm.

Figure 3 and 4: Regression analysis for leptospirosis (blue graph) and dengue (green graph) vs

the amount of rainfall

Dengue Leptospirosis

Pearsons Correlation 0.615 0.233

Sig. (2-tailed) 0.142 0.631

Table 4. Pearsons correlation coefficient and significance in between dengue and rainfall;

leptospirosis and rainfall

The correlation between rainfall and dengue as indicated by the Pearson's Correlation

Coefficient is 0.615 indicating a positive moderate relationship between the two. While, Linear

Regression in figure 3 shows that there is a positive correlation between the two factors. It can

then be inferred that there is a direct relationship between the amount of rainfall and the

prevalence of dengue. On the other hand, the correlation of leptospirosis and rainfall is 0.233

showing a positive weak relationship. Similar with the result for dengue and rainfall, regression

analysis shows that there is a positive correlation between the two. Thus, there is a weak

relationship between leptospirosis and the amount of rainfall. In the National Capital Region of

the Philippines, there is only a moderate yet positive correlation between dengue and the amount

of rainfall and a weak positive one for leptospirosis and rainfall considering that the data set used

in this study are the average amount of precipitation and occurrence of dengue during the wet

season.

Since both r values are greater than the Cronbach Alpha used which is 0.05, the

relationship between both diseases and rainfall are not significant. This evidence therefore shows

that the null hypothesis stating that there is no relationship between the two diseases is supported.

However, this does not show a strong proof to confirm the null hypothesis as further studies and

verification is still needed. There is a possibility that in the NCR the prevalence of the two

diseases is independent of the amount of rainfall. Still it can be noted that rainfall can still affect

the prevalence of these two diseases as signified by the positive correlation between them.

Although, it is not the sole and strongest factor that determines the occurrence of the said diseases

in the NCR. Thus, preventive measures against these two life-threatening diseases must be

utilized by people living or frequenting NCR during both the rainy and dry seasons.

ACKNOWLEDGEMENTS

We would like to thank the Department of Biology and Mr. Howell Ho in imparting us

knowledge in the usage of different statistical methods that is to be used in this study.

CONCLUSION

Given the Pearsons correlation coefficient (r), it is proven that no significant relationship

exists between the occurrence of Dengue and Leptospirosis with the amount of rainfall in the

Philippines. The weather, therefore, does not influence the prevalence of Dengue and

Leptospirosis within the population. This implies that, regardless of the season, whether wet or

dry, Filipinos must take the necessary precautionary measures to prevent acquiring these

illnesses. Some of the steps to take in order to avoid infection would be: the application of anti-

mosquito lotion and covering up any exposed wounds.

REFERENCES

Gubler DJ, Clark GG, 1995. Dengue/Dengue Hemorrhagic Fever: The Emergence of a Global

Health Problem. Emerging Infectious Diseases [Internet]. Vol 1, No 2.

Adler B, Moctezuma ADLP, 2010. Leptospira and Leptospirosis. Veterinary Microbiology

[Internet]. Volume 140, Issues 3-4.

Disease Surveillance Report. Department of Health Website. [cited 2014 Oct 11]. Available from:

http://doh.gov.ph

J Epidermal Community Health, 2004. Relation of Rainfall pattern and epidemic leptospirosis in

the Indian state of Kerala. [cited 2014 Oct 11].

Jaroensutasinee, 2013. Distribution, seasonal variation & dengue transmission prediction in

Sisaket, Thailand. Indian Med Res 130 pp. 347-353