Posted by: genetika21 | 8 November 2007

Spatial risk factors analysis of humans cases of H5N1 virus infections in Indonesia.

L. Loth[1], J. Weaver[2], M.M. Hidayat[3]


Highly pathogenic avian influenza (HPAI) outbreaks in poultry in Indonesia were first reported in 2004 and the disease is now endemic in large parts of the country. Figure 1 shows Indonesia in Asia. The first case of human infection with H5N1 virus in Indonesia was confirmed in July 2005. Since 2005, cases of H5N1 virus infection have continued to occur, and up to July 2007, 100 people had been infected, with 80 fatalities. The descriptive epidemiology of human H5N1 infections was reported from July 2005 through June 2006. This poster analyses the spatial risk factors for H5N1 in humans in Indonesia.

Materials and Methods

Human case classification was assigned according to World Health Organisation (WHO) H5N1 case definitions . The number and location of human cases was retrieved from the WHO website. The data recorded the location of the patients at sub-district level. Point features were created using polygon centroids.

The Indonesian census data of 2005 recorded the number of human habitants per village. No census data was available for the island of Nias, west of the Sumatra coast, some smaller islands and the provinces of North Maluku and Papua. After converting the village polygon features data to point features, kernel smoothing was applied using an output raster of one square kilometre (km2) and a bandwidth of three kilometres.

Livestock data recorded poultry numbers by province . Poultry density is calculated by combining the total number of layer poultry, broilers and backyard (domestic) poultry in the province divided by the surface area of the province.

HPAI in poultry surveillance data was recorded by participatory disease surveillance (PDS) teams. PDS teams interview farmers searching for evidence of clinical outbreaks consistent with HPAI in poultry using a clinical outbreak definition that includes sudden death and high mortality. When active outbreaks are encountered where severely sick birds, or recently deceased carcasses are present, the PDS teams carry out an influenza type A rapid test (Anigen© test). A clinical outbreak consistent with HPAI and a positive rapid test in affected poultry is considered a confirmed detection of HPAI. The PDS teams are equipped with handheld Global Positioning Systems (GPS) devices and the exact location of the visit is recorded.

First order effects were analyzed and described. Simple unconditional association between the human cases of H5N1 virus infections and human population and poultry density were examined. The Pearson’s Chi-squared Test for Count Data was used analysing human cases by province. The statistical significance was 2-tailed and was set at P = .05. The temporal and spatial associations between infected humans and HPAI outbreaks in poultry were explored. Buffers with 1 kilometre, 500 meters and 250 meters radius were created around each human case and poultry HPAI outbreaks in these buffers were identified. The time of the human case was compared with the HPAI outbreak date.

Geographical Information System software was used to produce the maps and to perform the spatial analysis.


Census data showed a total population of 193 million people. Human density was highest on the island of Java with a population density between 6,000 and 100,000 per km2 . The 100 human cases were spatial represented by 57 point features (Figure 2). The highest number of human cases per point feature was nine (Karo, North Sumatra). Most human cases were recorded in the province of West Java (28, total population 34 million) and the city of Jakarta (25, total population 8 million) Figure 3 shows the location of human cases projected on the smoothed human population per km2. Figure 4 shows this again but only for the island of Java. Pair wise comparison of human case rates of the province of West Java and the city of Jakarta with all other provinces did not show significant associations.

Figure 6 shows the poultry density per square kilometre by province. Poultry densities are high (>700/km2) in the islands of Java and Bali. Poultry density is low in the city of Jakarta (400/ km2). The highest poultry density was present in the province of West Java (14,000/ km2). There is a significant difference comparing the human cases/ poultry density ratio of Jakarta and West Java.

Between January 2006 and July 2007, HPAI was detected in backyard poultry 2370 times (Figure 7 and Figure 8 and Figure 9). Seven HPAI outbreaks in poultry where within a 1 km radius of the 57 human cases point features. Two HPAI outbreaks were within (500 meters and) 250 meters of a human case. No temporal association of human disease and poultry outbreaks was found.


The data presented is not representative of the overall HPAI disease situation in Indonesia as there are spatial and temporal biases. PDS teams have been only active in 184 district of a total of 444 districts. PDS started in January 2006, while human cases have been recorded since July 2005.

Most people infected with H5N1 virus lived in the West of Java, more specifically in or around the capital Jakarta. The lack of significant association at province level for human case rates shows that the human population density is not a risk factor for human H5N1 infections.

Most poultry, commercial and backyard, were also found in the greater Jakarta area, but not in Jakarta city itself. The interpretation of the statistical significance of a human case/ poultry population density ratio is difficult and probably not useful. The contradictory results of low poultry densities in Jakarta city with a high number of human cases can be explained by the transportation of large number of live (infected) poultry into Jakarta markets. Poultry density is very likely a risk factor for human H5N1 infections, but further study is needed to confirm this hypothesis.

The lack of association between H5N1 infection in humans and HPAI in poultry was explained by A) an effective human disease surveillance system and a less effective animal disease surveillance system. HPAI in poultry is often investigated after the reporting and confirmation of disease in humans. Due to the time gap, disease in poultry is at this stage anecdotal and cannot be confirmed by diagnostic tests. B) Many people get infected not from contact with their own poultry but by buying infected poultry meat at markets relatively far from their homes. More spatial analysis is recommended for the future to identify other risk factors to help in more targeted preventions such as public awareness campaigns and risk based surveillance.


1. Sedyaningsih, E.R., Isfandari, S., Setiawaty, V., Rifati, L., Harun, s., Purba, W., Imari, S., Giriputra, S., Blair, P.J., Putnam, S.D., Uyeki, T.M., Soendoro, T. Epidemiology of cases of H5N1 virus infection in Indonesia, July 2005–June 2006. Journal of Infectious Diseases. 2007;196 (15 August) 2007 [cited 20 July 2007; Available from: .

2. WorldHealthOrganization. WHO case definitions for human infections with influenza A(H5N1) virus. 2007 [cited 20 July 2007]; Available from: .

3. WorldHealthOrganization. Avian influenza—situation in Indonesia—update 20 2007 [cited 20 July 2007]; Available from:

4. Statistik Peternakan. 2006 ed, Jakarta: Direktorat Jenderal Peternakan Departemen Pertanian RI.

5. ESRI®, ArcMap™ 9.1, Copyright © 1999-2005 ESRI Inc.

[1] Food and Agricultural Organisation of the United Nations, Avian Influenza, Indonesia, author for correspondence: mobile phone +62 81510520038, email:

[2] Food and Agricultural Organisation of the United Nations, Avian Influenza, Indonesia

[3] Directorate General of Livestock Services, Ministry of Agriculture, Indonesia


  1. Congratulations Andi.🙂

  2. thanks Jim

  3. saha jim teh wa?

  4. rerencangan kang

  5. rerencangan ti mana eta………..

    bener kenal teu ? kade can kenal geus poho…

    alus tulisan teh ndi, tapi peternak urang bingung macana, soalna urang nu ditanya sarua bingung…..

    pokona alus lah, terus narulis…….. !

  6. Hi! I was surfing and found your blog post… nice! I love your blog. 🙂 Cheers! Sandra. R.

  7. Thanks. We look forward to hearing from you again and for your opinions on the world of work.

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