Analysis of Malaria Incidence, Altitude, and Rainfall a Study in the Timor Tengah Selatan (TTS) District, West Timor, Indonesia ERMI NDOEN* AND TITIK RESPATI.

Slides:



Advertisements
Similar presentations
Use of Weather and Climate information in Climate risk management Example of ACMAD-IFRCC collaboration ACMAD by Léon Guy RAZAFINDRAKOTO.
Advertisements

Forecasting Malaria Incidence in Botswana Using the DEMETER Data Simon Mason International Research Institute for Climate and Society The Earth Institute.
Introduction to modelling extremes
AGENZIA REGIONALE PER LA PROTEZIONE DELLAMBIENTE DELLA SARDEGNA ARPAS Andrea Motroni Climate, climate change and desertification.
Global Precipitation Precipitation averages just about 1 meter per year over Earth but, like wealth, varies widely from place to place and from time to.
Climate Change Health Impacts and Adaptation Strategies Joacim Rocklöv, Associate Professor Epidemiology & global health, Umeå University
Ulisses E. C. Confalonieri Roberta Costa Dias Ulisses E. C. Confalonieri Roberta Costa Dias Climate Variability, Land Use and Malaria in the Amazon: Preliminary.
Climate and Hydrological and Extremes in Lake Victoria Basin An Assessment of Vulnerability and Adaptation to Climate Variability and Change Impacts on.
Vulnerability and Adaptation to Climate Change-Induced Malaria and Cholera in the Lake Victoria Region (AF91) P.Z. Yanda, R.Y.M. Kangalawe, R.J. Sigalla.
An Assessment of the Impact of Climate Features on Dengue Fever and its Vectors in Five Caribbean Countries (AIACC Project) By S C Rawlins PhD, Emeritus.
ENVIRONMENTAL CHANGE AND MALARIA IN MAROUA, FAR NORTH CAMEROON NDI Humphrey NGALA, Ph.D. Department of Geography ENS, University of Yaounde 1 Yaounde,
+ Environmental Factors and Risk Areas of West Nile Virus in Southern California, 2007–2009 Hua Liu & Qihao Weng Ivonna Reda.
The potential effects of climate change on malaria in tropical Africa using regionalised climate projections European Geosciences Union (EGU) General Assembly.
Hay et al Climate Change and Malaria  Climate warming  Increase in malaria outbreaks?  Re-emergence of other vector born diseases?  Mosquitoes.
ITCZ Aim- Describe and account for rainfall patterns across West Africa.
Climate Induced Migration and Urban Vulnerability in Eastern Himalayas Dr Sohel Firdos Associate Professor Dept. of Geography Sikkim University INDIA Hamburg.
Nidal Salim, Walter Wildi Institute F.-A. Forel, University of Geneva, Switzerland Impact of global climate change on water resources in the Israeli, Jordanian.
Health Aspect of Disaster Risk Assessment Dr AA Abubakar Department of Community Medicine Ahmadu Bello University Zaria Nigeria.
The Effect of Climate on Infectious Disease
International Tropical Convergence Zone
Understanding Drought
Presentation to Pre-Sessional Consultations on the IPCC TAR Milan, Italy November 2003 BRIAN CHALLENGER ANTIGUA AND BARBUDA.
Protecting our Health from Climate Change: a Training Course for Public Health Professionals Chapter 5: Policy Responses to Address the Health Risks of.
 Climate is average of weather conditions for 30+ years  Climatologists employ many different tools to organize the wealth of information about earth's.
First Session of South Asian Climate Outlook Forum (SASCOF – 1) Pune, India, April 2010 Impact of Extreme Climate Events on Maldives Abdul Muhsin.
Comparison of spatial interpolation techniques for agroclimatic zoning of Sardinia (Italy) Cossu A., Fiori M., Canu S. Agrometeorological Service of Sardinia.
The new HBS Chisinau, 26 October Outline 1.How the HBS changed 2.Assessment of data quality 3.Data comparability 4.Conclusions.
Using My NASA Data to Explore Earth Systems Lynne H. Hehr John G. Hehr University of Arkansas Department of Geosciences And Center for Math and Science.
Modelling of malaria variations using time series methods Ali-Akbar Haghdoost MD, Ph.D. in epidemiology and biostatistics faculty of Medicine, and Physiology.
1 By the end of this topic you should be able to:  explain with the aid of an annotated diagram, why Tropical latitudes receive more of the sun’s energy.
Trends and spatial patterns of drought incidence in the Omo-Ghibe River Basin, Ethiopia Policy Brief Degefu MA. & Bewket W.
Climate Change Tendencies in Georgia under Global Warming Conditions Mariam Elizbarashvili 1 Marika Tatishvili 2 Ramaz Meskhia 2 Nato Kutaladze 3 1. Ivane.
SOCIO-ECONOMIC IMPACT OF DROUGHT IN INDONESIA 2003 AND ITS HANDLING IN ACCORDANCE WITH POVERTY ALLEVIATION APPROACHES NATIONAL COORDINATING BOARD FOR.
INTER-TROPICAL CONVERGENCE ZONE (ITCZ).
An Application of Field Monitoring Data in Estimating Optimal Planting Dates of Cassava in Upper Paddy Field in Northeast Thailand Meeting Notes.
Presented by Binaya Pasakhala Assessing Vulnerability of People’s Livelihood in Far-western Nepal: Implications on Adaptation to Climate Change.
Public Health and Ecological Forecasting Ben Zaitchik Johns Hopkins University.
What is Geography?.  More than just map skills!
Talking Points 9/6/2005. Background  In our continuing efforts to make sound water management decisions, the scientists and engineers at SFWMD have been.
Vulnerability and Adaptation Kristie L. Ebi, Ph.D., MPH Executive Director, WGII TSU PAHO/WHO Workshop on Vulnerability and Adaptation Guidance 20 July.
Ouagadougou, Burkina Faso, (am) July 2013 Role of Standardisation in tackling the issues of climate change using ICTs in Africa Peter Ulanga, Universal.
Climate Change-Related Priorities. Turkmenistan Almaty
DOMESTIC ENVIRONMENT AND SOCIO-ECONOMIC FACTORS OF TUBERCULOSIS IN BANDUNG AND WEST TIMOR TITIK RESPATI GILARSI.
FACTORS ASSOCIATED WITH THE PATTERN OF DENGUE HAEMORRHAGIC FEVER (DHF) INCIDENCE IN INDONESIA ERMI NDOEN 1), TITIK RESPATI 1), PUSPARINI 2), ANA M LIMBONG.
Dr Mark Cresswell Impacts: Disease 69EG6517 – Impacts & Models of Climate Change.
Climate Change and Uganda
A REPORT ON AGRICULTURE IN UGANDA:. COUNTRY PROFILE: Uganda is located in the eastern region of Africa. It is bordered by Sudan in the north, Kenya in.
ASSESSMENT OF THE ANNUAL VARIATION OF MALARIA AND THE CLIMATE EFFECT BASED ON KAHNOOJ DATA BETWEEN 1994 AND 2001 Conclusions 1. One month lag between predictors.
Water scarcity and drought: examples of management in France Istanbul, 16 March 2009 Jean-Paul Rivaud MEEDDAT/DGALN/DEB.
1. Session Goals 2 __________________________________________ FAMINE EARLY WARNING SYSTEMS NETWORK Become familiar with the available data sources for.
The Threat of Dengue Fever - Assessment of Impacts and Adaptation to Climate Change in Human Health in the Caribbean An AIACC Project at The University.
III. Measures of Morbidity: Morbid means disease. Morbidity is an important part of community health. It gives an idea about disease status in that community.
Indicators for Climate Change over Mauritius Mr. P Booneeady Pr. SDDV Rughooputh.
Impacts of Flooding and Flood Risk 1)To study the impacts of flooding 2)To understand how hydrologists try to forecast the likelihood of future floods.
Air Masses and ITCZ. Topic 4: Air Masses and ITCZ Global wind circulation and ocean currents are important in determining climate patterns. These are.
Desert environments in Namibia their formation, location and climate
Tayba Buddha Tamang Meteorology/Hydromet Services Division Department of Energy Ministry of Economic Affairs South Asian Climate Outlook Forum (SASCOF-1)‏
Advanced Science and Technology Letters Vol.31 (MulGraB 2013), pp Effect of Urbanization on Climate.
DISCUSSION Demographic and Housing Status of the Respondents. Out of the 3456 respondents to the BES survey in TTS district, 93 TB cases were found and.
Modelling of malaria variations using time series methods
Water Insecurity and IWRM in West Timor, Indonesia
WASH and Cholera Preparedness to Response-
Modelling of malaria variations using time series methods
By KWITONDA Philippe Rwanda Natural Resources Authority
Inna Khomenko, Oleksandr Dereviaha
Seasonal variations of Onchocerciasis vector Simulium damnosum sensu lato in AbuHamed and Galabat foci in Sudan Arwa Elaagip B. Sc. (honors), M. Sc., PhD.
Climate in Brazil: present and perspective for the future
José J. Hernández Ayala Department of Geography University of Florida
Chapter 3.3 – Studying Organisms in Ecosystems
Overview Exercise 1: Types of information Exercise 2: Seasonality
Presentation transcript:

Analysis of Malaria Incidence, Altitude, and Rainfall a Study in the Timor Tengah Selatan (TTS) District, West Timor, Indonesia ERMI NDOEN* AND TITIK RESPATI GILARSI**

Introduction In Indonesia, malaria is one of the killer diseases along with TB. WHO estimates that the malaria burden in Indonesia is about 6 million clinical cases and 700 deaths per year (Laihad, 2000). Now, more than 43 million people live in malaria endemic areas. The Annual Malaria Report in 1998 showed that there were more than 3.5 million clinical cases of malaria with 300 deaths in Indonesia (Laihad, 2000). The numbers of malaria blood examinations were 1,851,819 slides, with 209,505 (11.31 %) positive slides (MOH of RI, 1999).

Malaria causes enormous problems, however the ability to overcome these problems is blocked by the scarcity of data and the lack of understanding of the situation. Detailed data of malaria risk and severity, and fundamental perspectives of where (distribution); why (environmental determinants); how (transmission intensity) and when (seasonality) malaria occur, do not exist or are very limited. Some of the potential environmental factors that are closely related to the malaria incidence are rainfall, temperature and humidity. The integration of those climate parameters with malaria incidence has become a point of concern for most scientists in the world.

This study will try to enhance the knowledge of the environmental risk factors that closely relate to malaria incidence. This study will try to deal with malaria problems by focusing on a specific area in regard to specific climate conditions. This could be an example of how to develop an instrument for defining some climate events that can be used to predict the potential of malaria endemic, and to adapt and implement it for the appropriate malaria control strategy. This study will also try to give sufficient information about environment health risk factors for malaria with regard to the formulation of malaria control and prevention policy in TTS District - NTT Province.

Aim This study will examine the association between environmental risk factors and the prevalence of malaria in TTS. Further, routine surveillance data of malaria cases will be correlated with altitude and rainfall information in order to see if seasonal patterns exist. In addition a simple geographical information system (GIS) mapping of malaria in TTS will be conducted to show the distribution of malaria incidence.

Area of Study This study was conducted in Timor Tengah Selatan (TTS) District. This district is one of the Fourteen Districts in the Province of Nusa Tenggara Timur, Indonesia. TTS District lies between East and – South. This district covers an area of km 2 or 8,33 % of the NTT Province. TTS District consists of 11 sub districts with a total of 200 villages. The TTS population based on the Indonesian Census of 2000 is 385,814 with 38,106 households.

Research Design and Methods This study is an ecological study. Data have been obtained from secondary resources. The institute or agencies which provided data are: TTS District Health Service; Bureau of Statistic of TTS District; The Planning and Development Bureau of TTS District; The Planning and Development Bureau of Nusa Tenggara Timur (NTT) Province, and Institute of Meteorology and Geophysics of NTT Province.

Data Collection Data were obtained from secondary sources. The data that were collected included: a. Malaria Incidence in TTS District from 1996 to Malaria data were collected from TTS Health Services District. The data shows the incidence of malaria at the village level. b. Weather Data (rainfall index, average humidity & temperature) in TTS District from 1996 to The weather data were collected from the Kupang Climatology Monitoring Station, NTT Province.

Data Analysis Several steps were taken to ensure the validity and clarity of the data. They include: a. Data Cleaning In the data cleaning process, data were recompiled and recounted in order to fill some missing data by using their average or the mean. b. Data Analysis - Spearman correlation The Spearman Rank correlation was used to establish the correlation between the weather conditions (rainfall, temperature and humidity) with the transmission of malaria in TTS district. In this analysis, the malaria incidence was transformed by one month lag. The Spearman correlation coefficient was obtained by using the SPSS version software.

Result Malaria Incidence The Health Center Report describes a high number of cases of malaria in all areas in Timor Tengah Selatan District, from 1995 to The number of cases of malaria tended to increase every year. There was a 68.5 % increase in the recorded malaria incidence from 1995 to The endemicity of malaria can be stratified by using Annual Malaria Incidence (AMI) standard. The level of AMI reflects the relative risk of malaria transmission or the susceptibility of malaria disease per 1,000 population.

Malaria is a seasonal disease. There was a variation in the transmission of malaria in TTS District from year to year. In 1995 the peak seasons for malaria transmission were in March to April and June to September. In 1996 there were three peak periods which were in February, April and July to September. In 1997, the transmission was quite stable from February to May. Afterwards, for 1998 to 2000, there was a changing of the peak transmission. In 1998, the high incidence seemed to move to June- September. In 1999 there was a high incidence in April, which reached a peak in June. And in 2000 the peaks of malaria transmission were from June to August. The pattern for the malaria peak transmission is not clear.

Altitude The TTS District contains a range of lowland and highland areas. In this study, the altitude data was not available for every village, except for those villages which have a rainfall station. This district has 9 rainfall monitoring stations. Each station is located at a different altitude. In this study, the villages which have rainfall stations were chosen as a representative area for further analysis.

Altitude and Malaria Incidence in TTS District Environmental and geographical factors are very considerable factors in malaria transmission and distribution. The areas of malaria distribution in the world roughly between 65 0 North and 40 0 South with the areas of altitude less than about 3,000 meters (Bailey, 1982). In general TTS District lies between East and – South. It is comprised of lowland and highland up to more than 1,000 meter. In regard to this geographical position, this district is the area where malaria is mostly perennial.

Another factor is that in the unstable areas, the dominant parasite is P. vivax (International Health Series, 1998). As mentioned before, P. vivax has a relapse or recrudescence characteristic (Oaks et al, 1991) which can increase the malaria incidences. Types of vegetation and irrigation systems are other factors that might be related with malaria in highland areas (Lindsay & Birley, 1996, cited in UNEP & WMO, 2001). In highland areas, there is more vegetation than in lowland areas. This condition is suitable for An barbirostris which is one of the main vector of malaria and which has a wide range distribution in Timor island (Webster, 2000).

Another possible factor that influences the occurrences of malaria in the highland areas, as in TTS District, is the progressive migration of mosquitoes from lower to higher altitude where the transmission is perennial. According to seasonal conditions, mosquitoes in lowlands can progressively move to the higher elevation areas. The seasonal conditions that can increase mosquito progression are warm and rainy weather (Leeson in Aron, 2001). MARA (1998) also noted that basically malaria incidence is lower in highland due to the lower temperature. However in Africa there is a lot of recent evidence that there is increasing malaria incidence in highland areas.

Factors that determine malaria incidence are diverse and complex but it is known that the environment plays an important role on the transmission of infectious diseases. The environmental factors that affect the distribution and incidence of malaria are rainfall, temperature and humidity (WHO, 1979; Sweeney, 1998; MARA, 1998; National Research Council, 2001). Malaria is also a seasonal disease. MARA (1998) also suggested that for a seasonal disease, knowing the duration of season (the start and the end of the season) is important to ensure the success of malaria control program because it influences the dynamic of malaria transmission.

Rainfall influences malaria transmission by providing mosquitoes with breeding places and increasing humidity which improves mosquito survival rates (WHO, 1979; MARA, 1998; Reid, 2000). In TTS District, there are 6 months of rainy season and 6 months of dry season with the range or rainfall index in generally from 10 mm to 135 mm. The malaria incidence pattern in shows that malaria was high in dry season. The highest peak transmission season was from June to September, while the lowest transmission was in rainy season, from November to January.

Many researchers have also found that malaria is usually absent in the wet season. In heavy rainfall, the water flow washes out the pools and other mosquito breeding places (Wijusundera, 1988, Aron, 2001). in Tanzania Lindsay (2000, cited in Aron, 2001) found that rainfall was associated with the reduction of malaria incidence. Marten (1999, cited in National Research Council, 2001) suggested also that the suitability of vectors habitat is determined by the minimum precipitation level. Similarly, in Amazon, Brazilian researchers found that more rainfall could inhibit the breeding of mosquitoes, although the correlation between rainfall and malaria incidence is still doubtful because the most transmission occurs at the beginning of rainy season (Aron, 2001).

TTS District is one of the areas in West Timor which experiences a lack of water problem during the dry season. To solve this problem, the government has built ponds as watering places and for storage of water during the dry season. These dug ponds can become new breeding places for mosquitoes. In the same way, water provided for irrigation can create new mosquito breeding places and reduce the mosquito’s dependency on rainfall (Aron, 2001). This is one of the possible factors that can explain why the malaria incidence can still increase in the dry season in this area. In Africa researchers also found that inundation of land, creating a water reservoir, can make people in the local area with no experience of malaria become more vulnerable to malaria.

Many, researchers have found that a wetter rainy season is more favorable for the transmission of malaria. In Zimbabwe, Taylor and Mutambu (1986, cited in Aron, 2001) found the transmission of malaria increased on from February to May which are the months of the rainy season. Rainfall is also major determinant factor of malaria in Gambia (Koram, 1991 in Aron, 2001). In India, the maximum malaria prevalence is from July to November, which coincides with the rainy season (Burman,( 2000). Burman stated that rain increases the atmospheric humidity and is fundamental to the relationship between mosquitoes and its breeding places.

Conclusion Malaria is one of the major health problems in Timor Tengah Selatan (TTS) District. The transmission of malaria in this area is perennial in 200 villages. Malaria in the highland areas in TTS District is unstable malaria, so that the transmission of malaria in this area varies from year to year. Generally, the transmission of malaria in this area is higher in the dry season. However, at the village level the malaria pattern is highly variable. The malaria incidence did not vary according to the altitude, except that malaria incidence was greatest in areas that were 850 m above sea level.

Recommendations 1. In this study, only two important factors have been used. These are environmental variables and malaria incidence. It has not used the other factors of malaria disease such as disease vector or mosquitoes or the domestic environmental variables and people’s behaviour. These should be included in future studies. Thus, a further study is needed to get a clear explanation about malaria and its relationship to climate conditions, vectors and social factors.

Recommendations (cont) 2. To properly identify the malaria problems, mapping of malaria endemic areas is a crucial thing that needs to be done in TTS District. Such maps can be useful for many reasons. They can be used to highlight areas that need intervention, or, they can be used as an early warning tool. 3. In order to improve the success of malaria programs, collaboration is needed between health sectors, other institutions and the community as the target of program. 4. For the sake of the people’s health and economic growth, it is absolutely necessary to put more attention on malaria programs which include community participation.

References